# Understanding the dynamics of financial and economic crises: a comprehensive analysis

Mekki Hamdaoui, Abderraouf Ben Ahmed Mtiraoui, Zohra Aroussi, Mounir Smida

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Mekki Hamdaoui, Abderraouf Ben Ahmed Mtiraoui, Zohra Aroussi, Mounir Smida. Understanding the dynamics of financial and economic crises: a comprehensive analysis. Cogent Social Sciences, 2025, 11, 10.1080/23311886.2025.2454740. [hal-04950052](https://hal.science/hal-04950052v1)

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# Understanding the dynamics of financial and economic crises: a comprehensive analysis

Mekki Hamdaoui, Abderraouf Mtiraoui, Zohra Aroussi & Mounir Smida

**To cite this article:** Mekki Hamdaoui, Abderraouf Mtiraoui, Zohra Aroussi & Mounir Smida (2025) Understanding the dynamics of financial and economic crises: a comprehensive analysis, Cogent Social Sciences, 11:1, 2454740, DOI: 10.1080/23311886.2025.2454740

**To link to this article:** https://doi.org/10.1080/23311886.2025.2454740

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# Understanding the dynamics of financial and economic crises: a comprehensive analysis

Mekki Hamdaoui, Abderraouf Mtiraoui, Zohra Aroussi and Mounir Smida

Economics, MOFID-University of Sousse, Sousse, Tunisia

## ABSTRACT

This paper aims to assess the nature of the link between financial and economic crises. To do this, we develop a continuous measure for crisis probability. The methodology employed distinguishes short- from long-term relationships, enhancing the analysis's depth and fortifying the results for autoregressive processes. The study addresses endogeneity and potential simultaneity between different crises using a sample of 49 developed and emerging countries spanning 1984–2016. The empirical investigation incorporates a simultaneous equation, Bayesian Model Averaging (BMA) approach, a Panel Autoregressive Vector (P-VECM), an Autoregressive Distributed Lag (ARDL) technique, as well as Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) methods. Findings indicate that while all crisis types may stem from unfavorable conditions, there exists a time lag in triggering and duration. Specifically, economic crises tend to be more persistent and are typically preceded by financial crises. Granger-causality test results support a robust bidirectional causality between financial and real difficulties, with the financial sector influencing the real economy more significantly. Moreover, the study reveals that the impact of economic volatility on financial stability is transient and lacks long-term significance. Conversely, the effect of a financial crisis on the real economy is enduring and remains significant in the long run. Additionally, exchange market volatility emerges as a crucial determinant for both financial and economic crises.

## IMPACT STATEMENT

Our interest in this paper is to focus in the interdependency between economic and financial spheres. In particular, we aim to participate in the construction of a supervisory platform for politicians and policymakers by sequencing the triggering order of any fragility both in financial or real sectors and specifying potential transmission channels. The idea is to increase preventive actions to reduce likelihood of systemic crises by quickly acting to separate the two spheres and reduce possible contagion.

## ARTICLE HISTORY

Received 28 September 2023

Revised 9 March 2024

Accepted 1 December 2024

## KEYWORDS

Financial and economic crises; Bayesian model averaging; Markov switching approach; P-VECM; ARDL; FMOLS and DOLS

## SUBJECT

Submission of new manuscript for evaluation

## 1. Introduction

In examining the historical impact of financial and economic crises on potential output, valuable insights and stylized facts emerge, offering a basis for scenario identification and policy recommendations. However, the consequence of the subprime crisis necessitates a reevaluation of conclusions drawn from historical assessments (Abadli et al., 2020). While some studies posit simultaneous origins of economic and financial crises, others suggest a chronological shift, indicating potential causality. Against this backdrop, our study aims to elucidate the mechanisms through which financial shocks impact the real sphere and how economic difficulties manifest in the financial sector, drawing on recent global vulnerabilities, notably the subprime crisis.

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The aftermath of the subprime crisis, still echoing in numerous countries, resulted in a profound global recession triggered by a severe financial crisis. A vicious cycle unfolded in the United States, marked by falling property prices, increased mortgage foreclosures, and the collapse of securitization transactions. This turmoil led to adverse feedback loops, intensifying downward pressure on housing prices and culminating in a wave of bankruptcies as financial institutions struggled to securitize risky mortgages.

The repercussions extended to consumer spending, reducing household savings and net assets, translating into lower consumer spending, declining company profitability, layoffs, increased unemployment, and an economic recession (Claessens et al., 2010; Furceri & Mourougane, 2009). As financial institutions faced losses, solvency problems triggered rapid deleveraging, forced asset sales, and a collapse in confidence. The opacity of balance sheets increased, contributing to the freezing of interbank markets and further sales of securities to raise funds.

While numerous countries managed to overcome this situation, its essence and implications persist as central topics of discussion and research. Varied perspectives exist, with some attributing the crisis to excessive global savings funneled through an unregulated shadow banking market, while others note a common rise in debt before the crisis (Krugman, 2009; Reinhart & Rogoff, 2008). The crisis's global spread was facilitated by financial openness and globalization, causing economic recessions, systemic banking crises, and falls in property and equity prices. Regardless of the similarities or differences, the crisis has been very costly for the real and financial sectors, especially for consumption and investment. Reinhart and Rogoff (2009) argue that, on average, real GDP has fallen from peak to peak by more than 9% and that the duration of the recession has averaged approximately two years. Moreover, unemployment rose by 7% points during the contracting phase.

Financial crises, though infrequent, incur high economic and social costs, sparking significant academic and political debate. Determinants and transmission modes remain debated, with some works emphasizing economic, financial, and institutional factors, while others highlight the role of defective resolution policies (Caprio & Klingebiel, 1997). Indeed, resolving one crisis can increase the likelihood of another. For example, the intensive and massive support of the financial sector by public funds can hamper the sustainability of public finance and the solvency of countries. In addition, the fragility of a sector will reduce the effectiveness of an intervention initiative. Our study aims to fill gaps in the literature by analyzing the dynamic independence between financial and economic vulnerabilities, distinguishing short- and long-term relationships through a continuous measure of crisis probability.

Existing attempts to assess financial crisis costs face challenges in accounting for structural causalities. While macroeconometric models could provide a rigorous approach, we favor VAR-type modeling, demonstrating significant effects of financial shocks on economic activity and vice versa using the generalized response functions method (Pesaran & Shin, 1998). Despite the acknowledged costs of previous crises, the medium- and long-term effects have not been extensively studied.

Our study extends previous research by examining both short- and long-term interactions and causality between economic and financial crises, employing a continuous variable for a panel of 49 countries (22 developed and 27 emerging) from 1984 to 2016. Utilizing a panel vector autoregression (P-VAR) model, we find that financial fragility generally precedes and interacts with economic crises. By combining the logit model with a continuous measure of crisis, we enhance the robustness of our conclusions, offering a nuanced understanding of the intricate relationship between financial and economic vulnerabilities.

This work is structured as follows: Section 2 provides an overview of the theoretical connection between the economic and financial spheres. Section 3 encompasses empirical evidence, beginning with a presentation of the methodology, followed by a discussion of results and interpretations, and including a description of the data and the rationale behind variable selection. Finally, in Section 4, we draw conclusions from the findings.

## 2. Literature review

The recent financial crisis, characterized by stock market declines, real estate price slowdowns, and interbank market paralysis, had profound effects on consumption and investment decisions (Spilimbergo
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et al., 2008). This analysis underscores the complex mechanisms through which the crisis impacted the real economy and how financial sector is affected by economic situation and vulnerabilities of borrowers.

## 2.1. Transmission of the financial fragility to the real economy

The nature of financial shocks, varying across crises, necessitates a comprehensive understanding of their transmission mechanisms. While changes in the cost of capital and interest rates play a role, the subprime nature of the shocks centralizes the financial sphere. The financial accelerator, acting as a vector, induces a fall in investment and consumption. Borrowers experience an external financing premium¹ tied to their financial situation, leading to restructuring effects favoring large companies over small ones.

The crisis's impact extends to securitization activity. Reduced possibilities in securitization revive the credit channel (Altunbas et al., 2009), coinciding with a decline in bank loans due to the risk of a loan portfolio adjustment. The crisis, starting in 2007, accentuates effects related to bank capital, defaults on real estate loans, illiquid structured products, and a decline in stock market values.

The recent global crisis amplifies uncertainty, influencing growth and employment outlooks. Heightened risk prompts businesses and households to adopt a cautious, wait-and-see approach. In the face of uncertainty, households increase savings for precautionary reasons, as seen in consumption equations linked to changes in the unemployment rate. For companies, the argument put forwards is linked to the irreversibility of investment spending (Pindyck, 1988). Since the decision is irreversible, the firm gives up the opportunity to invest in order to do so at a more opportune time. The overall uncertainty around the macroeconomic situation should therefore encourage companies to postpone their investment decisions, thus slowing demand and production.

Consumption decisions are intricately tied to the wealth effect, grounded in Friedman's theory of permanent income. Individuals, with wealth derived from salary, financial assets, and real estate, experience lasting consumption changes in response to shocks. The perceived permanence of negative shocks significantly reduces permanent income and, consequently, leads to enduring decreases in consumption.

Theoretical perspectives on financial crises' impact on production highlight uncertainties in medium-term labor market participation. Factors include discouragement of job seekers, early retirements, and potential shifts in the structural unemployment rate. Long jobless spells affect skills, contributing to hysteresis effects (Blanchard & Wolfers, 2000; Nickell et al., 2005).

Financial crises induce a prolonged depression in capital accumulation by restricting credit supply, imposing stricter lending standards, and increasing effective borrowing costs (Bernanke & Gertler, 1989). Asset price declines further hinder corporate balance sheets and collateral values (Kiyotaki & Moore, 1997). Total factor productivity faces ambiguity, with potential negative impacts on innovation and research and development spending during difficult times (Guellec & van Pottelsberghe de la Potterie, 2001).

In the aftermath of a financial crisis, the process of reallocation can adversely affect both the level and the rate of growth of total factor productivity. This point of view is generally accepted since the crisis lastingly slowed down certain activities such as financial services, construction and industry. Thus, these transformations can affect total factor productivity through a compositional effect. They can lead to a limited industrial sector that is characterized by a high rate of productivity growth in favor of the development of the service sector, which is less labor intensive. Likewise, a slow restructuring process due to structural rigidities or credit constraints can affect total factor productivity. The delay in processing toxic assets and the restarting of the banking sector or an ineffective subsidy policy can lead to strict credit conditions for companies with a strong innovative capacity, potentially profitable and with prospects for growth. However, ill-structured banks can support businesses that are unprofitable but hold more political pressure or can fear not being bailed out by the government in the event of major difficulties. This type of loan leads to an inefficient reallocation of capital at the expense of innovative but vulnerable companies and to a slow industrial restructuring of large companies, which are more likely to be politically protected against bankruptcy (Caballero et al., 2006).

Total productivity growth could sustain permanent damage due to reduced innovative activities stemming from pro-cyclical private investment behavior (Guellec & van Pottelsberghe de la Potterie, 2001). The relationship between crisis-induced reduction in expected returns on research and development and
its impact on innovation is likely protracted. The deferral of key investments in innovation could have lasting effects on productivity and growth.

The role of 'learning by doing' in the growth process suggests that recessions, characterized by skill loss during periods of unemployment, can have enduring consequences. Activities fostering production and productivity are complementary, and the reduction in the growth rate may persist over the long run (Martin & Rogers, 2000).

This comprehensive analysis provides insights into the multifaceted ways financial crises traverse through the economy, impacting various sectors, behaviors, and long-term productivity. We can therefore draw the following hypothesis:

H₁: Financial fragility exerts a negative influence on the real sector, and this impact may endure over an extended period.

## 2.2. Transmission of economic difficulties to the financial sector

Financial crises are often viewed as consequences of economic deterioration, with indicators such as stock market performance reflecting the state of the real economy. This connection between economic fundamentals and financial sector health has been extensively explored in the literature (Caprio & Klingebiel, 1996; Demirgüc-Kunt & Detragiache, 1998; Gorton, 1988).

Historically, events like the Great Depression have shown that economic downturns, marked by falling raw material prices, unemployment, and declining household consumption, can lead to solvency crises for borrowers and, subsequently, financial institutions. In this context, banking crises can result from insolvency problems, with losses exceeding a bank's equity (Caprio & Klingebiel, 1997). This phenomenon is exacerbated in an ineffective regulatory environment.

In addition to the effect of financial liberalization, internal and external macroeconomic factors play crucial roles in financial stability (Gonzalez-Hermozillo, 1999). Internally, the business cycle, pricing policies (interest rates, inflation), and fiscal policy influence agent solvency and financial sector stability. Externally, current account imbalances, terms of trade, and exchange rate depreciation are key considerations.

Inflation, often a consequence of expansionary monetary policies, can distort decision-making in the credit market. High or unstable inflation makes it challenging for agents to assess risks accurately, hindering investment and solvency analysis. Conversely, a sudden reduction in inflation reduces nominal income and cash flows for financial institutions, increasing liquidity and solvency risks. The phenomenon of 'debt-deflation' or overindebtedness due to deflation, as described by Fisher (1933), can contribute to insolvency crises.

Rising interest rates, particularly short-term rates, are often precursors to banking crises (Mishkin, 1996). Borrowers, especially those with variable-rate loans, become more vulnerable with increased interest rates. The bank, forced to refinance at higher rates, faces heightened maturity risk. Financial liberalization, by promoting credit market competition, may contribute to a credit boom and increased credit risk.

High central government spending and budget deficits can erode confidence in a country's economic situation. A budget deficit may trigger a crisis of confidence among credit market participants, affecting perceptions of banks' solvency and leading to massive fund withdrawals, thereby precipitating a liquidity crisis.

Current account imbalances, often indicated by deficits, can be problematic and have macroeconomic implications (Obstfeld, 2012). Inflows of foreign funds may contribute to moral hazard, with poorly managed institutions obtaining financing (Corsetti et al., 1999; Giannetti, 2007). Exchange rate depreciation and the stability of the fixed exchange rate system are identified as factors affecting the risk of financial crises (Domaç & Martinez-Peria, 2003; Duttagupta & Cashin, 2011; Husain et al., 2005).

Private capital flows, especially in emerging markets, can exhibit a boom-bust phenomenon (Goldfajn & Valdes, 1997). Inflows contribute to a credit boom and potential overinvestment, while outflows can lead to liquidity crises and exchange losses. The Asian crisis is illustrative of how capital flow behaviors can trigger financial crises, transmitting illiquidity from one institution to another.
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This literature review suggests that a comprehensive understanding of financial crises requires consid-
ering a myriad of economic and macroeconomic factors. The following formulated hypothesis provides a
basis for empirical investigations into the dynamics of economic difficulties and their transmission to the
financial sector.

H₂: A decline in economic activity heightens the risk of a lasting financial crisis.

**2.3. Interdependence between financial and economic spheres**

The complex relationship between financial and economic spheres has been a subject of extensive exploration in economic literature. Various perspectives and theories have been developed to understand the interplay between financial events and the broader economic landscape.

Allen and Gale (2007) contribute to the ongoing debate on financial crises by distinguishing between models that perceive crises as the result of mass behavior (self-fulfilling prophecies) and those considering crises as intrinsic parts of the business cycle, resulting from shocks to fundamentals. Minsky (1982) adds a critical perspective, arguing that crises are inherent to capitalism. In prosperous economic times, riskier decisions are often made, leading to behaviors that can contribute to speculative bubbles and, ultimately, financial instability.

Two prominent schools of thought—monetarist and classical—offer distinct explanations for the rela-
tionship between the economic cycle and financial crises. The classical perspective views financial crises
as random events unrelated to economic activity, often attributed to 'mass hysteria' or 'crowd psychology'
(Diamond & Dybvig, 1983). In contrast, monetarists propose that fluctuations in the financial sector are
natural extensions of the business cycle. According to this view, economic downturns reduce the value
of assets, increasing the likelihood of agents being unable to meet their liabilities and triggering panics
or crises.

A significant body of literature focuses on the role of financial channels in transmitting monetary policy measures to economic activity. Financial accelerator models elucidate how changes in the cost of external resources, influenced by monetary policy, impact investment, consumption, and the overall economic trajectory. These models highlight the dynamic nature of the financial accelerator, where changes in asset prices, interest rates, and credit markets contribute to cyclical swings in the real economy (Bernanke et al., 1999).

The financial accelerator models, pioneered by Bernanke and Gertler (1989), play a crucial role in
explaining how financial events impact the real economy (Bernanke et al., 1999; Kiyotaki & Moore, 1997).
These models explicitly establish a connection between the cost of external financing, self-financing, and
economic fluctuations (Bordo & Haubrich, 2010; Céspedes et al., 2004; Kannan, 2012; Mendoza, 2010;
Schneider & Tornell, 2004). They introduce the concept of information asymmetries and limited commit-
ments, emphasizing the role of borrowers' balance sheets in shaping economic outcomes. In this context,
borrowers' wealth and equity become pivotal factors influencing investment decisions and credit limits.
In imperfect economic environments, macroeconomic and financial variables interact through wealth and
substitution effects. Credit market changes, reflected in asset prices, impact consumption, investment,
and resource allocation. However, perfect market models dismiss the significance of credit market shocks,
implying only a minor role in explaining economic cycles.

The financial accelerator introduces feedback mechanisms between the financial and real sectors, leading to potentially asymmetric effects on the business cycle. In times of economic downturns, a rise in financing difficulty amplifies the impact of the financial accelerator, creating a powerful negative feedback loop. Conversely, during economic recovery, improved balance sheets and reduced external funding premiums contribute to a more gradual return to internal funds. Borrowers then need sufficient internal capital to attract and retain financing for investment projects (Kooli et al., 2022). Bernanke and Gertler (1989) show that the optimal financial contract, in the presence of information asymmetries, involves an agency cost resulting from the need to control and audit borrowers, both of which are costly for the lender². A high self-financing borrower is not only less dependent on external financing, but also experiences a low premium on external funds. Therefore, there is an inverse relationship between the
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well-being of borrowers and their investment costs. In a dynamic investment model, this feedback between the agency cost of investment and the borrower's net worth creates a mechanism by which shocks to economies are amplified and propagated through their effects on borrowers' cash flow. For example, consider an unfavorable productivity shock that lowers the current cash flow. This induces a great need for external financing, increasing the premiums of the external funds of firms and, consequently, the cost of the new investment. Declining investment slows economic activity and revenues in subsequent periods, amplifying and propagating the effects of the initial shock over time.

The intricate relationship between the financial and economic spheres continues to be a subject of ongoing research and debate. The integration of financial accelerator models and considerations of information asymmetries has enriched our understanding of how financial events reverberate through the broader economy. Future research may delve deeper into refining these models, considering additional factors such as direction of effects and persistence of interdependencies, policy responses, and the evolving nature of financial markets. A nuanced comprehension of these interactions is crucial for policymakers, economists, and market participants to navigate the complexities of modern financial systems. For this, our main purpose in this work is to test the following hypothesis:

H₃: The interaction between financial and economic spheres is undeniable, yet the intensity, direction, and duration of their effects vary over time.

## 3. Empirical framework

The early body of literature indicates that various forms of crises may share common roots in economic vulnerabilities, but their chronological sequence is determined by the propagation mechanism, influencing the order of occurrence. Building on the insights of Jemovic and Marinkovic (2021), who propose that a negative shock affecting production units can lead to a cascade of consequences, including reduced state tax revenues, compromised bank asset quality, and the emergence or worsening of external imbalances, our focus is on assessing and elucidating potential connections between financial and economic crises. This encompasses understanding the order of triggering, propagation dynamics, and the logic of potential causality.

Empirical findings align with theoretical intuitions, as exemplified by Dell'Ariccia et al. (2008), highlighting that real sectors in countries strongly linked to external finance are more profoundly impacted by credit crises. A financial crisis, negatively influencing the real economy, not only has direct budgetary implications but also contributes to fiscal imbalances due to increased expenditures for social reasons in the wake of a diminished tax base. Moreover, if the government has guaranteed bank debt through deposit insurance schemes, the crisis could lead to additional claims. As public debt reaches a critical threshold, it becomes unsustainable, compelling the government, already involved in resolving the banking sector, to implement austerity measures. This, in turn, slows domestic demand and investment, raises unemployment rates, and elevates the risk of borrower insolvency and liquidity crises, ultimately deteriorating the quality of bank assets and yields. According to Reinhart and Rogoff (2014), countries undergoing banking crises are prone to experiencing debt and economic crises. In a similar vein, Jemovic and Marinkovic (2021) contend that countries exposed to public debt face the risk of insolvency if the government loses its ability to refinance its debt.

### 3.1. Methodological background

The objective of this study is to discern the origins of financial and economic crises and investigate the intricate relationship between the real and financial spheres. A comprehensive understanding of this dynamic is crucial for formulating effective policies to mitigate the social repercussions associated with impending crises. To achieve this, a diverse set of models, including simultaneous equations, Bayesian Model Averaging (BMA), and Vector Error Correction Model (VECM), are employed. The analysis is based on two measures of crises: discrete measures capturing the nature of the link between economic and financial spheres, and the family of Markov switching regression, which utilizes the probability of crises as an outcome.
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The methodology involves computing the probability of both financial and economic crises using coefficients estimated through multinomial logit models. Building on the work of Dabrowski et al. (2016), this approach addresses challenges related to signal extraction and qualitative variables models, paving the way for a new avenue in financial and economic crisis literature. Recognizing potential simultaneity between financial and economic crises, initial analyses involve regressing simultaneous equations to gain preliminary insights into potential determinants of each crisis type.

For the identification of early warning indicators, we adopt the BMA approach, which determines factors for use in VECM analysis to study their interactions with corresponding crises. Following the methodology outlined by Jemovic and Marinkovic (2021), an autoregressive vector model is employed, emphasizing the importance of time series models to explore interdependencies and potential causality in the realm of financial and economic crises.

Our research encompasses a comprehensive sample of 49 developed and emerging countries, as outlined in Table A1. The inclusion of major global economies, influential in shaping international policies, ensures coverage of significant crises in recent decades. The temporal scope of our study is primarily dictated by data availability, specifically the political risk measure from ICRG, and data on financial crises from the databases developed by Laeven and Valencia (2020) and Nguyen et al. (2021). Given that none of the countries in our sample has encountered a financial crisis beyond 2015 and the availability of political risk data from 1984 to 2016, we deliberately selected this time frame. We deemed it worthwhile to extend the period up to the present, particularly considering the potential impact of the COVID-19 pandemic, which could introduce substantial changes to the results.

To gauge potential early warnings of financial crises, we selected a set of variables widely acknowledged by economists either individually or collectively (Alessi & Detken, 2011; Dawood et al., 2017; Frankel & Saravelos, 2012; Kaminsky & Reinhart, 1999; Rose & Spiegel, 2011). A detailed list and description of these candidate variables are provided in Table A2. Given the contemporary trend in crisis modeling, we adopt a model averaging approach, a recommended strategy for addressing challenges in identifying determinants of events (Babecký et al., 2014; Crespo-Cuaresma & Slacik, 2009; Feldkircher & Zeugner, 2009; Fernández et al., 2001; Hamdaoui, 2016; Moral-Benito, 2011; Sala-I-Martin et al., 2004). This method offers the advantage of considering uncertainty and determining optimal combinations of variables by assigning weights and classifying models based on their fit.³

## 3.2. Data

There is no universally accepted definition of a systemic financial crisis, but the widely employed characterization comes from Claessens et al. (2005). They describe a systemic crisis as a situation where a country's corporate and financial sectors witness a significant number of defaults, encountering substantial challenges in meeting contractual obligations on time. This scenario leads to a sharp rise in nonperforming loans, depleting most or all of the aggregate banking system's capital. Such a crisis may coincide with depressed asset prices, such as equity and real estate values, notable increases in real interest rates, and a deceleration or reversal in capital flows. Previous literature has identified various variables as potential determinants of financial crises. For instance, Bussiere (2013) highlights international reserves and exchange rate depreciation, while Kaminsky and Reinhart (1999) focus on the domestic credit growth rate for banking and currency crises. Levy-Yeyati and Panizza (2011) emphasize real per capita GDP as an indicator of insolvency and debt crisis probability. Frankel and Saravelos (2012) identify determinants of the subprime crisis, with a focus on exchange rate appreciation. However, these studies typically treat each type of crisis independently, overlooking potential interactions or simultaneity between financial instability and challenges in the real economy. Reinhart and Rogoff (2009) distinguish between quantitative (exchange) and qualitative crises (banking and debt) and specify conditions for each. A monetary crisis involves a speculative attack on the currency leading to devaluation, substantial spending of international reserves, increased interest rates, or the imposition of capital controls. An external debt crisis occurs when a country struggles to service its external debt, while a domestic public debt crisis arises when a country fails to meet its national budgetary obligations. Systemic banking crises involve actual or potential bank failures requiring public intervention.
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This study adopts the classifications from Laeven and Valencia (2020), a widely recognized reference database on various financial disturbances, including banking crises, globally. They establish criteria for defining different types of crises, including banking, exchange, and debt crises, drawing on specific indicators and events. For a banking crisis, they consider two key conditions: significant signs of financial distress and substantial public interventions. Financial distress is identified through factors such as bank runs, losses, or liquidations, with severity indicated by nonperforming loans exceeding 20% of total loans or significant closures of 20% of the banking system. Public interventions, constituting a crisis, involve measures like deposit freezes, bank holidays, nationalizations, and fiscal restructuring costs exceeding 5% of GDP. Similarly, an exchange crisis is characterized by a sharp nominal depreciation against the U.S. dollar, meeting specific thresholds, such as a year-on-year depreciation of at least 30% and at least 10% points higher than the depreciation rate in the year before. For debt crises, events like a country declaring a moratorium, restructuring agreements, or obtaining a major IMF aid program signify a crisis. Sovereign debt default or restructuring is tracked using data from various sources, including Beim and Calomiris (2001), World Bank (2002), Sturzenegger and Zettelmeyer (2006), IMF Staff reports, and media reports. In summary, the authors provide clear criteria and rely on well-established definitions and sources to identify and date episodes of financial, banking, exchange, and debt crises in their analysis. The financial crisis variable categorizes a country as undergoing a financial crisis if it is currently facing any of the specified crises—be it banking, exchange, or debt crises. In other words, the occurrence of any one of these crisis types is deemed indicative of the country experiencing an overarching financial crisis.

To gauge the economic situation, we rely on World Bank data pertaining to GDP at a constant price, with the aim of eliminating the cyclical effect from the trend through the Hodrick-Prescott filter method. Our definition of an economic crisis centers on a scenario marked by a current wealth level falling below the trend. Consequently, we have devised a binary variable denoting the state of the real economy. This variable assumes a value of 1 in the event of a crisis and 0 otherwise. In the subsequent discussion, we outline the rationale behind introducing distinct variables to elucidate various crisis types, commencing with the financial crisis.

### 3.2.1. Financial crisis

Capital account liberalization, often associated with increased capital flows and heightened competition, may raise the risk of financial crises when capital movements reverse. Consequently, we introduced the variable 'FL' as a proxy for capital account openness.

Exchange rates play a pivotal role in financial crisis models due to their impact on external financing costs, solvency of borrowers, capital flows, trade volume, and current account balance (Babecký et al., 2014; Hamdaoui et al., 2022; Lestano et al., 2003). However, the real exchange rate is not able to reflect all pressures on national money (Jemovic & Marinkovic, 2021). In addition, the international reserve ratio is used many times as an indicator of liquidity, indicating national economies' ability to provide sufficient liquidity (Dawood et al., 2017; Frankel & Saravelos, 2012; Hamdaoui, 2016; Lestano et al., 2003). In this context, we consider the following variables: real effective exchange rate (REER), current account balance (CACCT), transactions of goods and services (TRADE), terms of trade change (TOTC), M2 to international reserve ratio (M2RES), and capital flow volumes (KFLOW).

The economic situation significantly influences agents' profits and solvability, affecting their ability to meet credit commitments, particularly in the banking sector. To capture these dynamics, we introduce variables such as economic growth rate (GDPG) and economic crisis (Ecoc) as determinants of financial crises. Additionally, increased public debt and expansionary fiscal policies are regarded as signs of mismanagement, contributing to a general solvency crisis (Jemovic & Marinkovic, 2021). Therefore, we incorporate variables like total debt (Debt), fiscal balance (Fiscal), and inflation (INFL).

Credit to the private sector is considered an indicator of flexible credit policy and high accumulated risk (Fielding & Rewilak, 2015). In addition to this frequently used indicator in financial crisis models, recent literature emphasizes the concept of excessive credit focusing on the growth rate instead of the volume of credit (Hume & Sentance, 2009). Hence, we include variables like credit to the private sector by banks (CPS) and domestic credit growth (DCG) to assess potential financial risk.
<figure><img src="image_20.png" /></figure>

Monetary aggregates, such as M2 to GDP, serve as indicators of liquidity and excessive risk-taking (Fouejieu, 2017). Accordingly, we consider the broad money-to-GDP ratio (Money) to evaluate liquidity levels and risk-taking. The real interest rate reflects a country's attractiveness to international funds and exposure to external risk (Qin & Luo, 2014). Hence, we introduce the variable real interest rate (RIR) as a potential determinant of financial difficulty.

Institutional quality indicators, such as GDP per capita (GDPC), provide insights into political and public policy effectiveness. Variables like depositary insurance scheme (DINS) and political risk (PR) help assess moral hazard behavior, political stability, and the efficiency of government interventions in stabilizing the financial sector (Breuer, 2004; Demirgüç-Kunt & Detragiache, 2005). Similarly, the political regime nature (PREG) is considered due to its impact on financial sector vulnerability, with democratic situations potentially reducing the probability of massive capital withdrawals compared to countries with poor institutional and political environments. In autocratic or anarchy regimes, insolvency procedures may be poorly designed or the judicial system is not able to deal with large-scale financial difficulty in addition to opaque decision-making processes and prevalent corruption (Marshall & Jaggers, 2007). Similarly, Lensink et al. (1999) supported that economic growth and financial difficulties depend largely on political stability, civil liberty and the perception of politics. Aisen and Veiga (2013) confirm these results, suggesting that political instability reduces investment decisions because of increased uncertainty and may lead to violence and legitimacy.

### 3.2.2. Economic crisis

The literature on economic growth underscores the multifaceted interplay of various factors influencing wealth creation at the country level, impacting both supply and demand. Key determinants include the volume of public expenditure, human capital formation, investment levels, the unemployment rate, exchange rates, and inflation. Additionally, non-economic and sociopolitical factors, such as government efficiency and political systems, along with demographic indicators like population growth, play pivotal roles (Acemoglu, 2009).

Trade openness has been recognized as a stimulant for economic growth in prior studies (Al-Raimony, 2011; Barro, 2003; Romer, 1990; Tekin, 2012). For instance, trade reforms are believed to foster technology transfer, competition, and access to international funds, thereby promoting economic growth (Edwards, 1992; Chang et al., 2009; Ynikkaya, 2003). Accordingly, the variable 'TRADE' is introduced to measure the relaxation or removal of trade barriers, and the current account balance 'CACCT' reflects the outcome of external transactions.

The impact of total government spending on economic growth lacks consensus in the literature. Some studies support the positive effects of government spending on education and human capital formation (Barro, 1991; Benos, 2009; Ghosh & Gregoriou, 2007; Sala-I-Martin et al., 2004), while others highlight potential negative effects, particularly related to inappropriate fiscal policies like military spending measures (Hou & Chen, 2014; Pieroni, 2009). The variable 'GSIZE' is used to assess the state's ability to stimulate economic activity and avoid economic difficulties and crises. Education, considered a pivotal factor in growth theory, is represented by the secondary school enrollment variable 'SCHOOL', serving as a proxy for workforce qualification, while population growth rate 'POPG' accounts for the potential effects of human capital on economic growth.

Investment is recognized as a critical factor influencing economic growth, and the variable 'INVEST' captures the contributions of private investment in stimulating industry and economic activities (Easterly & Rebelo, 1993). Additionally, the financial sector's role in financing economic activities is acknowledged (Levine & Zervos, 1998; Beck et al., 1999; Rousseau & Wachtel, 2000), and indicators like credit to the private sector ('CPS') and domestic credit growth ('DCG') are chosen to account for these effects. Additionally, we introduced the variable ('M2RES') to gauge the ratio of money and quasi-money to total international reserves, aiming to assess the potential risk of massive capital flight and the government's capacity to respond to exchange rate pressure.

Likewise, investment decisions are negatively affected by uncertainty, and factors like high inflation or exchange rate volatility make investor expectations challenging. The variables real effective exchange rate ('REER') and inflation ('INFL') account for the potential effects of price instability on agents' attitudes toward risk.
Beyond traditional determinants, economic growth and stability may be influenced by public policies, including political, administrative, and institutional systems. For instance, governance quality has been identified as a significant factor affecting economic growth (Arusha, 2009). Considering the broader context, property rights, regulatory frameworks, and conflict resolution systems are recognized as key determinants of economic growth, alongside social and macro-stabilization policies (Acemoglu et al., 2002; Mauro, 1995). In this regard, we incorporated the political regime variable ('PREG') to account for the impact of political systems on economic growth. Democratic regimes are often associated with wider property rights, judicial efficiency, and law adherence, fostering the installation of new projects and economic growth (Mauro, 1995; Murphy et al., 1993). Corruption, as an indicator of governance quality, has been shown to have a negative impact on economic growth by hindering innovation and technology transfer (Shera et al., 2014; Svensson, 2003). Thus, political risk ('PR') is included as a composite indicator representing bureaucracy, corruption, law and order, serving as a proxy for governance and institutional quality in the economic model.

### 3.3. Results and discussions

#### 3.3.1. Discrete analysis⁴

In the preliminary analysis of our data before conducting regression, we aimed to assess multicollinearity among explanatory variables. We employed two commonly used techniques: the correlation matrix and Variance Inflation Factors (VIFs). The correlation matrix facilitated a pairwise examination of variable correlations, with a coefficient exceeding 0.5 considered indicative of potential multicollinearity issues. Additionally, we calculated VIFs by determining $(1-R^2)$ for each regression and assessing the degree of independence of each variable from others through $(1/(1-R^2))$. A VIF value greater than or equal to 10, or an average VIF exceeding 2 (Kutner et al., 2004), suggests strong correlation and potential multicollinearity. If neither of these two conditions is met, the impact of multicollinearity is not worrisome, and all the explanatory variables can be simultaneously introduced in the model without distorting the results.

For the analysis of financial crisis determinants (Table 1), the variable 'GDPC' exhibited strong correlations with 'FI', 'CPSB', and 'PR'. Consequently, we opted to exclude 'GDPC' from the regression to mitigate multicollinearity concerns. Furthermore, 'CPSB' displayed strong correlation with 'Money', prompting its exclusion from the analysis. These decisions were informed by the elevated VIF values associated with these variables. Despite observing correlations greater than 0.5, the robustness of our conclusions regarding financial crisis determinants remains unaffected since none of the corresponding VIFs exceeded 10, and the average VIF remained below 2 even before excluding the specified variables. Therefore, any combination of these variables is possible without flawing or affecting the robustness of our conclusions regarding the determinants of the financial crisis.

It seems that some variables such as TRADE, TOTC, M2RES and KFLOW share similar components inside. We recognize the importance of addressing concerns related to shared components and overlapping information in the chosen indices. However, the decision to use these variables in their original form, rather than decomposing them into real values, was guided by considerations of consistency with established literature and methodologies widely accepted in the field. Retaining these variables in their original form aligns with traditional practices and ensures practical interpretability for policymakers and practitioners accustomed to working directly with these measures.

To address multicollinearity concerns, the careful assessment of VIFs was conducted for all included variables. While VIFs provide a measure of multicollinearity, we acknowledge that they do not offer a theoretical explanation for the inclusion of specific variables as themselves. Nevertheless, our decision was made to maintain consistency with established practices and ensure the practical relevance of our findings. In this case, the models to be estimated are as follows:

$$ \text{Fincit} = a_1 + a_2 \text{Ecocit} + a_3 \text{FLit} + a_4 \text{GDPGit} + a_5 \text{CACCTit} + a_6 \text{DCGit} + a_7 \text{TOTCit} + a_8 \text{KFLOWit} + a_9 \text{M2RESit} \\ + a_{10} \text{INFLit} + a_{11} \text{REERit} + a_{12} \text{RIRit} + a_{13} \text{PREGit} + a_{14} \text{DINSit} + a_{15} \text{PRit} + a_{16} \text{TRADEit} + a_{17} \text{MONEYit} \\ + a_{18} \text{Debtit} + a_{19} \text{Fiscalit} \quad (1) $$
<figure><img src="image_21.png" /><figcaption>Table 1. Correlation matrix (financial crisis candidate variables).</figcaption></figure>

<table><thead><tr><th></th><th>FinC</th><th>EcoC</th><th>FL</th><th>GDPG</th><th>CACCT</th><th>DCG</th><th>CPSB</th><th>TOTC</th><th>KFLOW</th><th>M2RES</th><th>INFL</th><th>REER</th><th>RIR</th><th>PREG</th><th>GDPC</th><th>DINS</th><th>PR</th><th>TRADE</th><th>BMoney</th><th>Debt</th><th>Fiscal</th></tr></thead><tbody><tr><td>FinC</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EcoC</td><td>-.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FL</td><td>-.10</td><td>.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GDPG</td><td>-.18</td><td>-.20</td><td>-.11</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CACCT</td><td>-.04</td><td>.14</td><td>.19</td><td>.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>DCG</td><td>-.04</td><td>-.12</td><td>.04</td><td>.09</td><td>-.09</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CPSB</td><td>-.04</td><td>.01</td><td>.51</td><td>-.07</td><td>.26</td><td>.04</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TOTC</td><td>.17</td><td>.15</td><td>-.01</td><td>-.26</td><td>.13</td><td>-.12</td><td>-.05</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>KELOW</td><td>-.08</td><td>-.10</td><td>.30</td><td>.07</td><td>.28</td><td>.01</td><td>.28</td><td>-.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>M2RES</td><td>.02</td><td>-.02</td><td>.34</td><td>-.16</td><td>-.09</td><td>-.02</td><td>.35</td><td>-.01</td><td>.21</td><td>-.03</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>INFL</td><td>.11</td><td>.03</td><td>-.15</td><td>-.15</td><td>-.02</td><td>-.09</td><td>-.08</td><td>.05</td><td>-.04</td><td>-.05</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>REER</td><td>.04</td><td>-.02</td><td>.03</td><td>.09</td><td>-.06</td><td>.02</td><td>.08</td><td>-.03</td><td>.02</td><td>.04</td><td>.04</td><td>.47</td><td>-.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>RIR</td><td>.16</td><td>.02</td><td>-.06</td><td>-.06</td><td>-.01</td><td>.05</td><td>-.01</td><td>-.01</td><td>-.01</td><td>-.01</td><td>.04</td><td>-.03</td><td>-.15</td><td>.02</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PREG</td><td>.01</td><td>.02</td><td>.26</td><td>-.16</td><td>-.18</td><td>-.07</td><td>.04</td><td>.05</td><td>-.05</td><td>.21</td><td>.21</td><td>-.03</td><td>-.03</td><td>.37</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GDPC</td><td>-.05</td><td>-.01</td><td>.68</td><td>-.19</td><td>.35</td><td>.09</td><td>.56</td><td>-.02</td><td>.28</td><td>.35</td><td>.35</td><td>-.09</td><td>-.03</td><td>-.03</td><td>.45</td><td>.35</td><td>1.0</td><td></td><td></td><td></td><td></td></tr><tr><td>DINS</td><td>.05</td><td>.04</td><td>.36</td><td>-.11</td><td>.07</td><td>.02</td><td>.14</td><td>-.01</td><td>.11</td><td>.18</td><td>.18</td><td>-.09</td><td>-.09</td><td>-.03</td><td>.38</td><td>.64</td><td>.35</td><td>1.0</td><td></td><td></td><td></td></tr><tr><td>PR</td><td>-.04</td><td>-.02</td><td>.56</td><td>.04</td><td>.04</td><td>.07</td><td>.46</td><td>-.04</td><td>.24</td><td>.20</td><td>.20</td><td>-.10</td><td>.09</td><td>-.02</td><td>.38</td><td>.64</td><td>-.02</td><td>.24</td><td>1.0</td><td></td><td></td></tr><tr><td>TRADE</td><td>-.05</td><td>-.08</td><td>.30</td><td>.11</td><td>.47</td><td>-.02</td><td>.37</td><td>.56</td><td>-.04</td><td>.24</td><td>.20</td><td>-.07</td><td>.01</td><td>-.04</td><td>-.30</td><td>.20</td><td>-.07</td><td>.32</td><td>.41</td><td>1.0</td><td></td></tr><tr><td>Money</td><td>-.05</td><td>.01</td><td>.35</td><td>.01</td><td>.25</td><td>-.02</td><td>.75</td><td>-.01</td><td>.41</td><td>.31</td><td>.31</td><td>-.08</td><td>.08</td><td>-.02</td><td>-.10</td><td>.34</td><td>.07</td><td>.32</td><td>.41</td><td>.09</td><td>1.0</td></tr><tr><td>Debt</td><td>.03</td><td>.08</td><td>.19</td><td>-.16</td><td>.01</td><td>-.08</td><td>-.01</td><td>.08</td><td>.07</td><td>.21</td><td>.21</td><td>.02</td><td>-.02</td><td>.08</td><td>.07</td><td>.11</td><td>.05</td><td>.06</td><td>.14</td><td>.09</td><td>.15</td></tr><tr><td>Fiscal</td><td>.03</td><td>.08</td><td>-.16</td><td>-.25</td><td>-.59</td><td>-.01</td><td>-.32</td><td>-.03</td><td>-.27</td><td>.08</td><td>.08</td><td>.02</td><td>.08</td><td>.01</td><td>.24</td><td>-.22</td><td>.02</td><td>-.20</td><td>-.51</td><td>-.25</td><td>.15</td></tr><tr><td>VIF</td><td></td><td>1.1</td><td>2.3</td><td>1.4</td><td>2.1</td><td>1.0</td><td>3.7</td><td>1.1</td><td>1.8</td><td>1.5</td><td>1.3</td><td>1.1</td><td>1.3</td><td>2.0</td><td>3.6</td><td>1.4</td><td>2.2</td><td>2.6</td><td>2.9</td><td>1.2</td><td>2.2</td></tr><tr><td>Mean VIF</td><td>1.9</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
$$ \begin{aligned} \text{Ecocit} = & a_0 + a_1 \text{Finci} + a_2 \text{FLit} + a_3 \text{CPSit} + a_4 \text{MERESit} + a_5 \text{INFLit} + a_6 \text{REERit} + a_7 \text{PREGit} \\ & + a_8 \text{PRit} + a_9 \text{TRADEit} + a_{10} \text{POPGit} + a_{11} \text{GSIZEit} + a_{12} \text{INVESTit} + a_{13} \text{SCHOOLit} \\ & + a_{14} \text{CACCTit} + a_{15} \text{DCGit} \end{aligned} \quad (2) $$

In examining the determinants of economic crises (Table 2), the correlation matrix reveals weak correlations among all variables, ensuring low Variance Inflation Factors (VIFs) (the highest being 2.4, which is < 10), with a mean VIF of 1.5, below the threshold of 2. Thus, the inclusion of these variables in the same model poses no concerns regarding reliability, result quality, or the interpretability of conclusions.

After excluding strongly correlated variables, we conducted simple regressions (simultaneous equations), carefully addressing the issues of endogeneity and simultaneity that may exist between financial and economic crises (Table 3). Our findings indicate that economic crises, independent of economic development and financial structure, do not act as genuine triggers for financial crises contrary to hypothesis 2. However, the occurrence of a financial crisis significantly elevates the likelihood of an economic crisis, particularly in emergent and market-based economies.

For the full sample, our observations reveal that capital account liberalization, economic growth, a current account surplus, and an increase in a country's liquidity significantly reduce the likelihood of a financial crisis. Conversely, deteriorating terms of trade, rising interest rates, and political instability increase the likelihood of financial vulnerability. While some determinants, like the economic growth rate, consistently moderate financial crises, certain variables lose significance depending on the country's nature, such as the capital account opening variable, which becomes insignificant for developed countries.

Regarding economic crises, we note that financial crises act as triggers for economic crises, similar to hypothesis 1, in the full sample, emergent, and market-based economies. Furthermore, increased credit to the private sector, political stability, heightened transaction volume, and investment reduce the likelihood of a genuine crisis in the full sample. However, democracy, increased public spending, and a current account surplus increase the likelihood of an economic crisis. The unexpected results, such as democracy (PREG) or an increase in general government expenditure (Gsize) triggering economic crises, prompt us to delve into a more nuanced analysis using models that differentiate between the short and long term. Our hypothesis posits that certain variables may exhibit dynamic and time-varying behaviors, indicating that the relationships between different variables are not static but change over time.

This in-depth exploration seeks to uncover the nuanced dynamics that underlie economic and financial crises, moving beyond static interpretations and considering the temporal evolution of these complex relationships.

The literature has grappled with the challenge of uncertainty regarding the selection of explanatory variables in a single model. The inclusion of numerous non-important variables can lead to inflated standard errors, while the sequential introduction of variables may result in the loss of important information

<table><caption>Table 2. Correlation matrix (economic crisis candidate variables).</caption><thead><tr><th></th><th>EcoC</th><th>FinC</th><th>FL</th><th>CPS</th><th>M2RES</th><th>INFL</th><th>REER</th><th>PREG</th><th>PR</th><th>TRADE</th><th>POPG</th><th>Gsize</th><th>INVEST</th><th>SCHOOL</th><th>CACCT</th><th>DCG</th></tr></thead><tbody><tr><td>EcoC</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FinC</td><td>-.01</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FL</td><td>.01</td><td>-.10</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CPS</td><td>.03</td><td>-.03</td><td>.49</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>M2RES</td><td>-.02</td><td>.02</td><td>.34</td><td>.38</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>INFL</td><td>.03</td><td>.11</td><td>-.15</td><td>-.08</td><td>-.03</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>REER</td><td>-.02</td><td>.04</td><td>.03</td><td>.09</td><td>.04</td><td>-.05</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PREG</td><td>.02</td><td>.01</td><td>.26</td><td>.06</td><td>.21</td><td>-.03</td><td>-.15</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PR</td><td>-.02</td><td>-.04</td><td>.56</td><td>.47</td><td>.20</td><td>-.10</td><td>.09</td><td>.38</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TRADE</td><td>-.08</td><td>-.05</td><td>.30</td><td>.28</td><td>-.04</td><td>-.07</td><td>.01</td><td>-.30</td><td>.24</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>POPG</td><td>-.05</td><td>.05</td><td>-.31</td><td>-.20</td><td>-.18</td><td>.07</td><td>.08</td><td>-.29</td><td>-.33</td><td>.04</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Gsize</td><td>.06</td><td>-.02</td><td>.30</td><td>.19</td><td>.26</td><td>-.09</td><td>.01</td><td>.36</td><td>.32</td><td>-.11</td><td>-.44</td><td>1.0</td><td></td><td></td><td></td><td></td></tr><tr><td>INVEST</td><td>-.24</td><td>-.04</td><td>-.08</td><td>.12</td><td>-.10</td><td>-.07</td><td>.07</td><td>-.25</td><td>.01</td><td>.15</td><td>.05</td><td>-.20</td><td>1.0</td><td></td><td></td><td></td></tr><tr><td>SCHOOL</td><td>.03</td><td>-.05</td><td>.57</td><td>.37</td><td>.28</td><td>-.05</td><td>-.09</td><td>.38</td><td>.52</td><td>.20</td><td>-.47</td><td>.55</td><td>-.12</td><td>1.0</td><td></td><td></td></tr><tr><td>CACCT</td><td>.14</td><td>-.04</td><td>.19</td><td>.20</td><td>-.09</td><td>-.02</td><td>-.06</td><td>-.18</td><td>.14</td><td>.47</td><td>-.02</td><td>-.06</td><td>-.05</td><td>.15</td><td>1.0</td><td></td></tr><tr><td>DCG</td><td>-.12</td><td>-.04</td><td>.04</td><td>.03</td><td>-.02</td><td>-.09</td><td>.02</td><td>-.07</td><td>.07</td><td>-.02</td><td>-.01</td><td>.01</td><td>.11</td><td>.02</td><td>-.09</td><td>1.0</td></tr><tr><td>VIF</td><td></td><td>1.0</td><td>2.0</td><td>1.7</td><td>1.3</td><td>1.0</td><td>1.1</td><td>1.8</td><td>2.0</td><td>1.8</td><td>1.4</td><td>1.7</td><td>1.2</td><td>2.4</td><td>1.4</td><td>1.0</td></tr><tr><td>Mean VIF</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<figure><img src="image_22.png" /><figcaption>Table 3. Simultaneous equation regression results.ª</figcaption></figure>

<table><thead><tr><th colspan="5">Dependent variable: financial crisis/endogenous variable: Economic crisis</th><th colspan="5">Dependent variable: Economic crisis/endogenous variable: Financial crisis</th></tr><tr><th></th><th>Full sample</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th><th></th><th>Full sample</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th></tr></thead><tbody><tr><td>EcoC</td><td>-.052<br>(.49)</td><td>.053<br>(.57)</td><td>-.092<br>(.38)</td><td>-.080<br>(.61)</td><td>-.042<br>(.60)</td><td>FinC</td><td>.691<br>(.00)</td><td>.866<br>(.15)</td><td>.932<br>(.00)</td><td>.348<br>(.18)</td><td>.634<br>(.02)</td></tr><tr><td>FL</td><td>-.027<br>(.00)</td><td>.001<br>(.86)</td><td>-.036<br>(.00)</td><td>-.034<br>(.00)</td><td>-.030<br>(.00)</td><td>FL</td><td>.016<br>(.30)</td><td>-.016<br>(.59)</td><td>.020<br>(.32)</td><td>.006<br>(.77)</td><td>.024<br>(.28)</td></tr><tr><td>GDPG</td><td>-.013<br>(.00)</td><td>-.010<br>(.03)</td><td>-.013<br>(.00)</td><td>-.017<br>(.00)</td><td>-.009<br>(.00)</td><td>CPS</td><td>-.001<br>(.04)</td><td>-.001<br>(.12)</td><td>-.002<br>(.04)</td><td>-.001<br>(.90)</td><td>-.001<br>(.01)</td></tr><tr><td>CACCT</td><td>-.005<br>(.09)</td><td>-.012<br>(.01)</td><td>-.002<br>(.55)</td><td>-.007<br>(.21)</td><td>-.005<br>(.22)</td><td>M2RES</td><td>-.001<br>(.14)</td><td>.001<br>(.90)</td><td>-.011<br>(.02)</td><td>.001<br>(.47)</td><td>-.001<br>(.11)</td></tr><tr><td>DCG</td><td>-.055<br>(.13)</td><td>-.033<br>(.52)</td><td>-.033<br>(.53)</td><td>-.187<br>(.01)</td><td>.009<br>(.98)</td><td>INFL</td><td>.008<br>(.15)</td><td>-.003<br>(.01)</td><td>.001<br>(.10)</td><td>.002<br>(.11)</td><td>.008<br>(.18)</td></tr><tr><td>CPSB</td><td></td><td></td><td></td><td></td><td></td><td>REER</td><td>.002<br>(.68)</td><td>.009<br>(.70)</td><td>-.001<br>(.83)</td><td>.007<br>(.24)</td><td>-.001<br>(.36)</td></tr><tr><td>TOTC</td><td>.316<br>(.00)</td><td>.220<br>(.15)</td><td>.328<br>(.00)</td><td>.201<br>(.01)</td><td>.510<br>(.00)</td><td>PREG</td><td>.116<br>(.03)</td><td>-.162<br>(.67)</td><td>.091<br>(.12)</td><td>.045<br>(.58)</td><td>.210<br>(.00)</td></tr><tr><td>KFLOW</td><td>.009<br>(.21)</td><td>.001<br>(.13)</td><td>.008<br>(.53)</td><td>.001<br>(.34)</td><td>.004<br>(.63)</td><td>PR</td><td>-.002<br>(.09)</td><td>-.001<br>(.63)</td><td>-.002<br>(.23)</td><td>-.005<br>(.77)</td><td>-.006<br>(.02)</td></tr><tr><td>M2RES</td><td>.001<br>(.03)</td><td>.002<br>(.59)</td><td>-.006<br>(.79)</td><td>.002<br>(.08)</td><td>.001<br>(.02)</td><td>TRADE</td><td>-.002<br>(.00)</td><td>-.006<br>(.00)</td><td>-.002<br>(.01)</td><td>-.002<br>(.05)</td><td>-.002<br>(.00)</td></tr><tr><td>INFL</td><td>-.003<br>(.18)</td><td>.001<br>(.09)</td><td>-.004<br>(.18)</td><td>-.002<br>(.02)</td><td>-.001<br>(.58)</td><td>POPG</td><td>-.042<br>(.16)</td><td>.005<br>(.92)</td><td>-.054<br>(.22)</td><td>.004<br>(.99)</td><td>-.042<br>(.29)</td></tr><tr><td>REER</td><td>.005<br>(.01)</td><td>.001<br>(.17)</td><td>.005<br>(.03)</td><td>.006<br>(.00)</td><td>-.007<br>(.89)</td><td>Gsize</td><td>.025<br>(.00)</td><td>.029<br>(.11)</td><td>.029<br>(.00)</td><td>.026<br>(.00)</td><td>.040<br>(.00)</td></tr><tr><td>RIR</td><td>.006<br>(.00)</td><td>-.003<br>(.90)</td><td>.006<br>(.00)</td><td>.009<br>(.00)</td><td>.007<br>(.00)</td><td>INVEST</td><td>-.041<br>(.00)</td><td>-.050<br>(.00)</td><td>-.037<br>(.00)</td><td>-.033<br>(.00)</td><td>-.051<br>(.00)</td></tr><tr><td>PREG</td><td>-.003<br>(.89)</td><td>.028<br>(.83)</td><td>.008<br>(.79)</td><td>-.019<br>(.57)</td><td>.007<br>(.83)</td><td>SCHOOL</td><td>.001<br>(.24)</td><td>.002<br>(.36)</td><td>.008<br>(.63)</td><td>.001<br>(.48)</td><td>-.004<br>(.79)</td></tr><tr><td>GDPC</td><td></td><td></td><td></td><td></td><td></td><td>CACCT</td><td>.012<br>(.00)</td><td>.024<br>(.03)</td><td>.009<br>(.07)</td><td>.015<br>(.02)</td><td>.010<br>(.08)</td></tr><tr><td>DINS</td><td>.003<br>(.88)</td><td>-.010<br>(.76)</td><td>-.003<br>(.91)</td><td>-.010<br>(.77)</td><td>.023<br>(.43)</td><td>DCG</td><td>-.128<br>(.12)</td><td>-.199<br>(.11)</td><td>-.023<br>(.84)</td><td>-.260<br>(.06)</td><td>-.044<br>(.66)</td></tr><tr><td>PR</td><td>.001<br>(.01)</td><td>-.003<br>(.82)</td><td>.002<br>(.00)</td><td>.009<br>(.19)</td><td>.002<br>(.01)</td><td>cons</td><td>1.33<br>(.00)</td><td>1.70<br>(.00)</td><td>1.43<br>(.00)</td><td>.851<br>(.00)</td><td>1.83<br>(.00)</td></tr><tr><td>TRADE</td><td>.007<br>(.05)</td><td>.002<br>(.00)</td><td>.003<br>(.54)</td><td>.001<br>(.01)</td><td>.003<br>(.58)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Money</td><td>-.005<br>(.04)</td><td>-.004<br>(.16)</td><td>-.005<br>(.21)</td><td>-.005<br>(.17)</td><td>-.006<br>(.15)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Debt</td><td>.005<br>(.02)</td><td>-.006<br>(.10)</td><td>.001<br>(.01)</td><td>.007<br>(.01)</td><td>.002<br>(.65)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fiscal</td><td>-.005<br>(.85)</td><td>-.004<br>(.924)</td><td>.001<br>(.68)</td><td>-.001<br>(.81)</td><td>-.002<br>(.9)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cons</td><td>-.042<br>(.83)</td><td>-.172<br>(.64)</td><td>-.268<br>(.34)</td><td>.024<br>(.94)</td><td>-.098<br>(.71)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Our approach is Instrumental variables and two-stage least squares for panel-data models. After conducting the Hausmann test for the fixed or random effect we use the two-stage least-squares within estimator.

by excluding relevant variables. In addressing this challenge, Bayesian Model Averaging (BMA) has emerged as a useful technique, as demonstrated by Sala-I-Martin et al. (2004) and Hamdaoui (2016). BMA provides an optimal combination of indicators by detecting potential variables from a large set. The 'Posterior Inclusion Probability (PIP)' statistic in BMA measures the importance of each variable, where high PIP values indicate robust indicators and low values suggest irrelevance. Kass and Raftery (1995) classify the significance of variables based on PIP values, ranging from weak to decisive⁵.

The 'Model Probability' (PMP) statistic in BMA aids in selecting the best-performing model with optimal variable combinations. In this study, BMA is employed to choose potential indicators of different crises and their best combinations. Variables selected through BMA are then utilized to compute crisis probabilities and explore potential causal links between financial disturbances and economic recession. BMA begins with a broad array of candidate variables, applying statistical methods to identify potential predictors of different events, as highlighted by Madigan and Raftery (1994) and Raftery (1995). The list of variables, along with their descriptions and sources, is detailed in Table A2.

The BMA results (Table 4) for the full sample indicate that the opening of the capital account and robust economic growth decrease the likelihood of a financial crisis. Conversely, the depreciation of the national currency and the rise in the real interest rate increase the likelihood of a financial crisis. Economic growth and the real interest rate level emerge as common determinants of financial crises. However, while there is an interaction between financial and economic crises in some countries, no significant
<table><caption>Table 4. BMA results.ª</caption><thead><tr><th rowspan="2">Variable</th><th colspan="8">Dependent variable: financial crisis</th><th colspan="8">Dependent variable: economic crisis</th></tr><tr><th>Full</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th><th>Variable</th><th>Full</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th><th>Variable</th><th>Full</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th></tr><tr><th></th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th><th>PIP</th><th>TM</th></tr></thead><tbody><tr><td>EcoC</td><td>.73<sup>-</sup></td><td>1.0</td><td>.97<sup>-</sup></td><td>1.0</td><td>.01<sup>-</sup></td><td>.00</td><td>.35<sup>-</sup></td><td>.00</td><td>.24<sup>-</sup></td><td>.00</td><td>FinC</td><td>.05<sup>-</sup></td><td>.00</td><td>.84<sup>-</sup></td><td>1.0</td><td>.07<sup>-</sup></td><td>.00</td><td>.09<sup>-</sup></td><td>.00</td></tr><tr><td>FL</td><td>1.0<sup>-</sup></td><td>1.0</td><td>.05<sup>-</sup></td><td>.00</td><td>.87<sup>-</sup></td><td>1.0</td><td>.89<sup>-</sup></td><td>1.0</td><td>.99<sup>-</sup></td><td>1.0</td><td>FL</td><td>.05<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.06<sup>-</sup></td><td>.00</td><td>.03<sup>-</sup></td><td>.00</td></tr><tr><td>GDPG</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0</td><td>1.0</td><td>.80<sup>-</sup></td><td>1.0</td><td>CPS</td><td>.03<sup>+</sup></td><td>.00</td><td>.06<sup>+</sup></td><td>.00</td><td>.03<sup>+</sup></td><td>.00</td><td>.14<sup>+</sup></td><td>.00</td></tr><tr><td>CACCT</td><td>.07<sup>-</sup></td><td>.00</td><td>.19<sup>-</sup></td><td>.00</td><td>.02<sup>-</sup></td><td>.00</td><td>.21<sup>-</sup></td><td>.00</td><td>.04<sup>-</sup></td><td>.00</td><td>M2RES</td><td>.08<sup>-</sup></td><td>.00</td><td>.20<sup>-</sup></td><td>.00</td><td>.07<sup>-</sup></td><td>.00</td><td>.03<sup>-</sup></td><td>.00</td></tr><tr><td>DCG</td><td>.04<sup>-</sup></td><td>.00</td><td>.14<sup>-</sup></td><td>.00</td><td>.03<sup>-</sup></td><td>.00</td><td>.55<sup>-</sup></td><td>.00</td><td>.02<sup>+</sup></td><td>.00</td><td>INFL</td><td>.04<sup>+</sup></td><td>.00</td><td>.09<sup>-</sup></td><td>.00</td><td>.11<sup>+</sup></td><td>.00</td><td>.03<sup>+</sup></td><td>.00</td></tr><tr><td>TOTC</td><td>1.0</td><td>1.0</td><td>.15<sup>+</sup></td><td>.00</td><td>1.0<sup>+</sup></td><td>1.0</td><td>.71<sup>+</sup></td><td>1.0</td><td>1.0<sup>+</sup></td><td>1.0</td><td>REER</td><td>.09<sup>-</sup></td><td>.00</td><td>.01<sup>-</sup></td><td>.00</td><td>.07<sup>+</sup></td><td>.00</td><td>.04<sup>+</sup></td><td>.00</td></tr><tr><td>KFLOW</td><td>.09<sup>+</sup></td><td>.00</td><td>.18<sup>+</sup></td><td>.00</td><td>.08<sup>+</sup></td><td>.00</td><td>.34<sup>+</sup></td><td>1.0</td><td>.04<sup>+</sup></td><td>.00</td><td>PREG</td><td>.03<sup>-</sup></td><td>.00</td><td>.10<sup>-</sup></td><td>.00</td><td>.03<sup>+</sup></td><td>.00</td><td>.11<sup>-</sup></td><td>.00</td></tr><tr><td>M2RES</td><td>.05<sup>+</sup></td><td>.00</td><td>.12<sup>+</sup></td><td>.00</td><td>.02<sup>+</sup></td><td>.00</td><td>.04<sup>-</sup></td><td>.00</td><td>.30<sup>+</sup></td><td>.00</td><td>PR</td><td>.05<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.11<sup>-</sup></td><td>.00</td></tr><tr><td>INFL</td><td>.04<sup>-</sup></td><td>.00</td><td>.45<sup>+</sup></td><td>.00</td><td>.02<sup>-</sup></td><td>.00</td><td>.03<sup>+</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>TRADE</td><td>.05<sup>-</sup></td><td>.00</td><td>.35<sup>-</sup></td><td>.00</td><td>.02<sup>-</sup></td><td>.00</td><td>.01<sup>-</sup></td><td>.00</td></tr><tr><td>REER</td><td>.75<sup>+</sup></td><td>1.0</td><td>.42<sup>+</sup></td><td>.00</td><td>.17<sup>+</sup></td><td>.00</td><td>.81<sup>+</sup></td><td>1.0</td><td>.05<sup>+</sup></td><td>.00</td><td>POPG</td><td>.04<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.08<sup>-</sup></td><td>.00</td><td>.04<sup>-</sup></td><td>.00</td></tr><tr><td>RIR</td><td>1.0<sup>+</sup></td><td>1.0</td><td>.26<sup>+</sup></td><td>1.0</td><td>1.0<sup>+</sup></td><td>1.0</td><td>.96<sup>+</sup></td><td>1.0</td><td>1.0<sup>+</sup></td><td>1.0</td><td>Gsize</td><td>.07<sup>-</sup></td><td>.00</td><td>.06<sup>-</sup></td><td>.00</td><td>.35<sup>+</sup></td><td>.00</td><td>.05<sup>+</sup></td><td>.00</td></tr><tr><td>PREG</td><td>.04<sup>+</sup></td><td>.00</td><td>.07<sup>+</sup></td><td>.00</td><td>.05<sup>+</sup></td><td>.00</td><td>.05<sup>+</sup></td><td>.00</td><td>.05<sup>+</sup></td><td>.00</td><td>INVEST</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0<sup>-</sup></td><td>1.0</td><td>1.0<sup>-</sup></td><td>1.0</td></tr><tr><td>DINS</td><td>.15<sup>+</sup></td><td>.00</td><td>.02<sup>-</sup></td><td>.00</td><td>.08<sup>+</sup></td><td>.00</td><td>.21<sup>+</sup></td><td>.00</td><td>.03<sup>+</sup></td><td>.00</td><td>SCHOOL</td><td>.01<sup>-</sup></td><td>.00</td><td>.02<sup>+</sup></td><td>.00</td><td>.12<sup>-</sup></td><td>.00</td><td>.04<sup>-</sup></td><td>.00</td></tr><tr><td>PR</td><td>.05<sup>+</sup></td><td>.00</td><td>.02<sup>+</sup></td><td>.00</td><td>.13<sup>+</sup></td><td>.00</td><td>.06<sup>+</sup></td><td>.00</td><td>.06<sup>+</sup></td><td>.00</td><td>CACCT</td><td>1.0<sup>+</sup></td><td>1.0</td><td>.35<sup>-</sup></td><td>.00</td><td>.99<sup>+</sup></td><td>1.0</td><td>.89<sup>+</sup></td><td>1.0</td></tr><tr><td>TRADE</td><td>.01<sup>-</sup></td><td>.00</td><td>.09<sup>+</sup></td><td>.00</td><td>.07<sup>-</sup></td><td>.00</td><td>.04<sup>+</sup></td><td>.00</td><td>.04<sup>-</sup></td><td>.00</td><td>DCG</td><td>.94<sup>-</sup></td><td>1.0</td><td>.65<sup>-</sup></td><td>1.0</td><td>.28<sup>-</sup></td><td>.00</td><td>.62<sup>-</sup></td><td>1.0</td></tr><tr><td>BMoney</td><td>.05<sup>-</sup></td><td>.00</td><td>.03<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.01<sup>-</sup></td><td>.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Debt</td><td>.03<sup>+</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td>.19<sup>+</sup></td><td>.00</td><td>.14<sup>+</sup></td><td>.00</td><td>.05<sup>-</sup></td><td>.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fiscal</td><td>.06<sup>-</sup></td><td>.00</td><td>.08<sup>-</sup></td><td>.00</td><td>.06<sup>-</sup></td><td>.00</td><td>.46<sup>-</sup></td><td>.00</td><td>.02<sup>+</sup></td><td>.00</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PMP</td><td></td><td>.31</td><td></td><td>.09</td><td></td><td>.28</td><td></td><td>.04</td><td></td><td>.28</td><td></td><td></td><td>.50</td><td></td><td>.17</td><td></td><td>.26</td><td></td><td>.31</td><td></td></tr></tbody></table>

relationship is observed in others. Moreover, terms of trade changes and capital account liberalization are crucial in emergent, bank-based, and market-based countries but are inconsequential in advanced economies.

Turning to the determinants of economic crises, the BMA results highlight that an increase in the share of private investments and the growth of domestic credit reduce the probability of triggering such crises, especially in the full sample and developed countries. Notably, the results of the inferential BMA method suggest a departure from the frequentist method of simultaneous equations, indicating that economic crises are no longer significantly dependent on financial crises in the most studied sample. However, recognizing the static nature of these techniques and their limitation in accounting for the temporal evolution of relationships, an extension of the analysis is undertaken to enhance the reliability of the results.

Our methodology involves leveraging the outcomes of the Bayesian Model Averaging (BMA) method for each type of crisis to conduct a nuanced analysis of the relationships between each crisis type and its potential determinants, as well as the interplay among different types of crises. To achieve this, we employ VAR panel regressions, focusing on the variables identified by the BMA method as crucial explanatory factors for various crises. Our objective is to scrutinize how each crisis type responds to fluctuations in its potential determinants and other forms of financial vulnerabilities, considering both short-term and long-term dynamics. The most appropriate method for this analysis is the Vector Error Correction Model (VECM), particularly the restricted VECM, contingent upon the characteristics of our data.

The decision to use the VECM model is contingent on certain criteria, notably whether all variables are integrated of order one (I(1)) and not integrated of order two (I(2)), and whether there is potential cointegration. If these conditions are met, the VECM model is suitable; otherwise, an unrestricted Panel-VAR is employed. This method serves as a powerful tool for scrutinizing the dynamics of financial crisis occurrences. We adopt two analytical approaches, the first of which relies on a binary indicator of the financial situation—a commonly used technique. However, this approach falls short of capturing the intermediate evolution of financial vulnerabilities, spanning from the initial signs of fragility to the onset of a crisis.

To address this limitation and fulfill the requirements for applying methods that distinguish between short-term and long-term situations (e.g. the Autoregressive Distributed Lag (ARDL) technique) and account for endogeneity in cointegrating models (e.g. Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) methods), we undertake a continuous analysis. This involves determining the probability of different crises based on the coefficients estimated using all the included variables (following correlation testing) through logit regression.⁶ This method not only overcomes criticisms related to the use of binary

<footnote>ªSigns (-) and (+) corresponds to post mean (PM) indicating the nature (the sign) of the relationship between variable to be explained and explanatory variable. TM implies top model and corresponds to the best combination.</footnote>
<figure><img src="image_23.png" /></figure>

variables but also allows us to assess long-term interactions and the response and causality between different indicators.

Before proceeding with the regressions, a unit root test is conducted to determine the most appropriate method for our analytical goals. This comprehensive approach ensures a thorough investigation into the relationships and dynamics surrounding various types of financial crises, considering both short-term fluctuations and long-term interactions among the identified determinants.

All the variables in our study exhibit stationarity in level or become stationary in the first difference, as indicated in Table 5. Specifically, these variables are stationary of order (1) and not of order (2), allowing us to employ Panel-VAR (P-VAR) or Vector Error Correction Model (VECM) based on the results of the cointegration test.

For the financial crisis model, our findings (Table 6) reveal that nine out of eleven statistics indicate cointegration at the 0.05 significance level. This implies a long-run relationship among the series. Even in the presence of short-run shocks that may impact individual variables, these variables would

<table><caption>**Table 5.** Unit root tests.</caption><thead><tr><th rowspan="2">Methods</th><th colspan="5">Financial crisis</th><th colspan="4">Economic crisis</th></tr><tr><th>ECOC</th><th>FL</th><th>D(FL)</th><th>GDPG</th><th>TOTC</th><th>REER</th><th>RIR</th><th>INVEST</th><th>D(INVEST)</th><th>CACCT</th><th>DCG</th></tr></thead><tbody><tr><td>Null: Unit root (assumes common unit root process)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Levin, Lin & Chu t*</td><td>.000</td><td>.451</td><td>.000</td><td>.000</td><td>.000</td><td>.033</td><td>.000</td><td>.002</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>Null: Unit root (assumes individual unit root process)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ADF – Fisher Chi-square</td><td>.000</td><td>.206</td><td>.000</td><td>.000</td><td>.000</td><td>.062</td><td>.000</td><td>.871</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>PP – Fisher Chi-square</td><td>.000</td><td>.172</td><td>.000</td><td>.000</td><td>.000</td><td>.138</td><td>.000</td><td>.920</td><td>.000</td><td>.000</td><td>.000</td></tr></tbody></table>

Note. values presented in the table are p-values¹⁰.

<table><caption>**Table 6.** Pedroni cointegration test.</caption><thead><tr><th colspan="11">Financial crisis</th></tr><tr><th colspan="11">Null Hypothesis: No cointegration</th></tr><tr><th></th><th colspan="2">Full sample</th><th colspan="2">Developed</th><th colspan="2">Emergent</th><th colspan="2">Bank</th><th colspan="2">Market</th></tr></thead><tbody><tr><td colspan="11">Alternative hypothesis: common AR coefs. (within-dimension)</td></tr><tr><td>Panel v-Statistic</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W- Stat</td><td>Stat</td><td>W- Stat</td></tr><tr><td></td><td>-47.9</td><td>-6.97</td><td>-41.8</td><td>-3.86</td><td>-40.9</td><td>-4.75</td><td>-30.9</td><td>-5.42</td><td>-16.1</td><td>-4.74</td></tr><tr><td></td><td>(1.0)</td><td>(1.0)</td><td>(1.0)</td><td>(.99)</td><td>(1.0)</td><td>(1.0)</td><td>(1.0)</td><td>(1.0)</td><td>(1.0)</td><td>(1.0)</td></tr><tr><td>Panel rho-Statistic</td><td>-2.48</td><td>-3.04</td><td>-11.4</td><td>-10.3</td><td>-2.54</td><td>-2.86</td><td>-2.55</td><td>-2.52</td><td>-2.19</td><td>-2.56</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.01)</td><td>(.00)</td></tr><tr><td>Panel PP-Statistic</td><td>-26.1</td><td>-26.0</td><td>-22.9</td><td>-20.8</td><td>-16.4</td><td>-13.4</td><td>-21.4</td><td>-20.9</td><td>-12.1</td><td>-14.7</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td></tr><tr><td>Panel ADF-Statistic</td><td>-8.24</td><td>-7.81</td><td>-20.2</td><td>-18.1</td><td>-14.1</td><td>-12.5</td><td>-15.9</td><td>-15.3</td><td>-11.0</td><td>-13.5</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td></tr><tr><td colspan="11">Alternative hypothesis: individual AR coefs. (between-dimension)</td></tr><tr><td>Group rho-Statistic</td><td>-1.38</td><td>-10.2</td><td>-10.2</td><td>(.00)</td><td>-1.57</td><td>(.05)</td><td>-1.87</td><td></td><td>-1.80</td><td>(.03)</td></tr><tr><td></td><td>(.08)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.05)</td><td>(.05)</td><td>(.03)</td><td></td><td>(.03)</td><td>(.03)</td></tr><tr><td>Group PP-Statistic</td><td>-41.0</td><td>-28.3</td><td>-24.1</td><td>-24.1</td><td>-24.1</td><td>-33.2</td><td>-33.2</td><td></td><td>-20.2</td><td>(.00)</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td></td><td>(.00)</td><td>(.00)</td></tr><tr><td>Group ADF-Statistic</td><td>-11.6</td><td>-24.8</td><td>-24.8</td><td>-5.08</td><td>-14.5</td><td>-6.47</td><td>-19.4</td><td>-5.88</td><td>-6.70</td><td>-7.68</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td></tr></tbody></table>

<table><thead><tr><th colspan="11">Economic crisis</th></tr><tr><th colspan="11">Null Hypothesis: No cointegration</th></tr><tr><th></th><th colspan="2">Full sample</th><th colspan="2">Developed</th><th colspan="2">Emergent</th><th colspan="2">Bank</th><th colspan="2">Market</th></tr></thead><tbody><tr><td colspan="11">Alternative hypothesis: common AR coefs. (within-dimension)</td></tr><tr><td>Panel v-Statistic</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td><td>Stat</td><td>W-Stat</td></tr><tr><td></td><td>-.972</td><td>-2.87</td><td>.170</td><td>-1.04</td><td>.467</td><td>-1.40</td><td>-.119</td><td>-1.58</td><td>.613</td><td>-1.42</td></tr><tr><td></td><td>(.83)</td><td>(.99)</td><td>(.43)</td><td>(.85)</td><td>(.32)</td><td>(.91)</td><td>(.54)</td><td>(.94)</td><td>(.26)</td><td>(.92)</td></tr><tr><td>Panel rho-Statistic</td><td>-.998</td><td>-1.74</td><td>-1.91</td><td>-2.28</td><td>-2.40</td><td>-3.08</td><td>-.198</td><td>-.722</td><td>-3.20</td><td>-3.51</td></tr><tr><td></td><td>(.15)</td><td>(.04)</td><td>(.02)</td><td>(.01)</td><td>(.00)</td><td>(.00)</td><td>(.42)</td><td>(.23)</td><td>(.00)</td><td>(.00)</td></tr><tr><td>Panel PP-Statistic</td><td>-6.82</td><td>-8.71</td><td>-4.82</td><td>-5.39</td><td>-5.96</td><td>-7.60</td><td>-4.19</td><td>-5.46</td><td>-6.25</td><td>-7.04</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td></tr><tr><td>Panel ADF-Statistic</td><td>-4.89</td><td>-5.62</td><td>-4.52</td><td>-5.08</td><td>-5.76</td><td>-6.47</td><td>-4.79</td><td>-5.88</td><td>-6.70</td><td>-7.68</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td><td>(.00)</td></tr><tr><td colspan="11">Alternative hypothesis: individual AR coefs. (between-dimension)</td></tr><tr><td>Group rho-Statistic</td><td>1.09</td><td>-.354</td><td></td><td></td><td>-.916</td><td></td><td>1.46</td><td></td><td>-1.66</td><td>(.04)</td></tr><tr><td></td><td>(.86)</td><td>(.36)</td><td></td><td></td><td>(.17)</td><td></td><td>(.92)</td><td></td><td>(.04)</td><td>(.04)</td></tr><tr><td>Group PP-Statistic</td><td>-8.31</td><td>-5.18</td><td></td><td></td><td>-7.49</td><td></td><td>-5.67</td><td></td><td>-6.56</td><td>(.00)</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td></td><td></td><td>(.00)</td><td></td><td>(.00)</td><td></td><td>(.00)</td><td>(.00)</td></tr><tr><td>Group ADF-Statistic</td><td>-4.67</td><td>-4.64</td><td></td><td></td><td>-5.94</td><td></td><td>-4.84</td><td></td><td>-7.34</td><td>(.00)</td></tr><tr><td></td><td>(.00)</td><td>(.00)</td><td></td><td></td><td>(.00)</td><td></td><td>(.00)</td><td></td><td>(.00)</td><td>(.00)</td></tr></tbody></table>
<figure><img src="image_24.png" /></figure>

eventually converge over time. Consequently, the suitable techniques for estimating both short-run and long-run relationships are Vector Error Correction Models (VECM). These models offer a robust framework for capturing the dynamics and interactions among the variables, considering both short-term fluctuations and the long-term equilibrium relationships. This analytical approach aligns with established economic principles and enhances the reliability of our findings⁷.

The findings in the study highlight several interesting dynamics between economic and financial crises across different types of economies (bank-based, market-based, developed, and emergent countries). Across all categories of countries, the coefficients associated with lagged variables indicating financial crises are consistently negative and statistically significant, as outlined in Table 7. This aligns with the works of Claessens et al. (2005) and Kaminsky and Reinhart (1999) who have highlighted the importance of historical experiences and crisis memory in shaping future crisis probabilities. This suggests that a country experiencing a financial crisis is less likely to face a new crisis in the subsequent years. This idea aligns with the notion of crisis resolution and the implementation of reforms such as, Reinhart and Rogoff (2009) discussed the aftermath of financial crises and the subsequent recovery. Notably, in the full sample and bank-based economies, an economic crisis reduces the probability of triggering a financial crisis in the following two years. This study's observation corresponds with Bussiere's (2013) emphasis on the role of domestic credit growth in banking crises. However, for developed countries, the economic crisis significantly increases the likelihood of a financial crisis in the next year, although this effect loses significance in the second year. This finding is interesting and may be connected to the nature of advanced financial systems. This is consistent with research suggesting that economic downturns can expose vulnerabilities in well-developed financial markets (Reinhart & Rogoff, 2009).

In emergent countries, experiencing an economic crisis significantly reduces the probability of a financial crisis only in the next year. Surprisingly, the effect of experiencing an economic crisis on the probability of a financial crisis is not significant in market-based economies. This lack of a significant short-term impact aligns with the idea that market-based economies might be more resilient to short-term economic shocks (Frankel & Saravelos, 2012).

In all models, there is evidence of a long-run relationship from economic instability to financial crisis, with the coefficients associated with the error correction term being consistently negative and significant. This suggests that, in the long run, economic instability contributes to the likelihood of a financial crisis. However, the short-run effect indicated by the Wald test is not significant for market-based economies, suggesting no immediate impact. This evidence is consistent with theories suggesting that economic instability can contribute to systemic issues in the financial sector over time (Kaminsky & Reinhart, 1999). The GDP growth rate (GDPG) is not significant in the short term for all subsamples, except for developed countries, but becomes a potential determinant of financial crises in the long run. This aligns with the idea that sustained economic growth is crucial for financial stability (Reinhart & Rogoff, 2009).

A key finding is that the effect of economic crises on financial crises is substantial and persistent, particularly in bank-based economies. Additionally, the effect of the interest rate is not transitory; a rise in the interest rate significantly increases the frequency of financial crises, and this effect persists in the long term across all samples. This persistent effect of the interest rate aligns with literature that emphasizes the role of monetary policy and interest rates in shaping financial stability (Qin & Luo, 2014). The depreciation of the exchange rate increases the likelihood of a financial crisis within the next two years. This finding corresponds to the extensive literature on the impact of exchange rate movements on financial vulnerabilities (Lestano et al., 2003; Frankel & Saravelos, 2012; Hamdaoui, 2016). It appears that in developed countries, financial crises are a consequence of economic crises, while in other economies, economic crises precede financial crises.

Regarding the occurrence of economic crises, our P-VECM model results reveal that the determinants vary based on economic structure and development which is consistent with the idea that different types of economies may exhibit distinct vulnerabilities and responses to economic shocks (Levy-Yeyati & Panizza, 2011). Unlike financial crises, countries experiencing economic crises may be more exposed to a new cycle of recession. For the full and emergent country samples, coefficients associated with the lagged economic crisis variable are positive and significant, indicating that economic crises are persistent and challenging to resolve. This resonates with research emphasizing the lingering effects of economic downturns (Reinhart & Rogoff, 2009). In bank-based systems, the effect is positive, and in market-based
<figure><img src="image_25.png" /><figcaption>Table 7. VECM results.</figcaption></figure>

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="4">Full sample</th><th colspan="4">Developed</th><th colspan="4">Emergent</th></tr><tr><th>LTIE<sup>11</sup></th><th>coef</th><th>Prob</th><th>Wald</th><th>LTIE</th><th>Coef</th><th>Prob</th><th>Wald</th><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th></tr></thead><tbody><tr><td rowspan="12">Financial crisis</td><td>ECT</td><td></td><td>.026</td><td>.00</td><td></td><td></td><td>-.042</td><td>.00</td><td></td><td></td><td>.030</td><td>.000</td><td></td><td></td></tr><tr><td>FINC(-1)</td><td></td><td>-.610</td><td>.00</td><td>533.2</td><td></td><td>-.698</td><td>.00</td><td>362.3</td><td></td><td>-.551</td><td>.000</td><td>231.0</td><td></td></tr><tr><td>FINC(-2)</td><td></td><td>-.265</td><td>.00</td><td>(.00)</td><td></td><td>-.281</td><td>.00</td><td>(.00)</td><td></td><td>-.277</td><td>.000</td><td>(.00)</td><td></td></tr><tr><td>ECOC(-1)</td><td>-.008</td><td>-.044</td><td>.00</td><td>13.2</td><td>-.634</td><td>.054</td><td>.03</td><td>6.47</td><td>-.163</td><td>-.057</td><td>.005</td><td>7.81</td><td></td></tr><tr><td>ECOC(-2)</td><td>(.00)</td><td>-.042</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.004</td><td>.82</td><td>(.03)</td><td>(.000)</td><td>-.016</td><td>.455</td><td>(.02)</td><td></td></tr><tr><td>FL(-1)</td><td>-.942</td><td>-.039</td><td>.03</td><td>8.24</td><td></td><td></td><td></td><td></td><td>-.911</td><td>-.040</td><td>.070</td><td>7.22</td><td></td></tr><tr><td>FL(-2)</td><td>(.00)</td><td>.029</td><td>.10</td><td>(.01)</td><td></td><td></td><td></td><td></td><td>(.000)</td><td>.041</td><td>.058</td><td>(.02)</td><td></td></tr><tr><td>GDPG(-1)</td><td>-.941</td><td>-.001</td><td>.94</td><td>.630</td><td>-1.02</td><td>.008</td><td>.03</td><td>13.9</td><td>-.920</td><td>-.004</td><td>.167</td><td>3.22</td><td></td></tr><tr><td>GDPG(-2)</td><td>(.00)</td><td>-.001</td><td>.61</td><td>(.72)</td><td>(.00)</td><td>.014</td><td>.00</td><td>(.00)</td><td>(.000)</td><td>-.004</td><td>.114</td><td>(.19)</td><td></td></tr><tr><td>TOTC(-1)</td><td>.008</td><td>.176</td><td>.08</td><td>14.8</td><td></td><td></td><td></td><td></td><td>-.010</td><td>.422</td><td>.000</td><td>13.2</td><td></td></tr><tr><td>TOTC(-2)</td><td>(.00)</td><td>.152</td><td>.03</td><td>(.00)</td><td></td><td></td><td></td><td></td><td>(.000)</td><td>.237</td><td>.004</td><td>(.00)</td><td></td></tr><tr><td>REER(-1)</td><td>-.893</td><td>.002</td><td>.00</td><td>6.32</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>.002</td><td>.00</td><td>(.04)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(RIR(-1)</td><td>-.778</td><td>-3E-6</td><td>.74</td><td>6.07</td><td>-1.00</td><td>.005</td><td>.02</td><td>6.52</td><td>-.732</td><td>9.4E-7</td><td>.939</td><td>5.98</td><td></td></tr><tr><td>(RIR(-2)</td><td>(.00)</td><td>2E-5</td><td>.03</td><td>(.04)</td><td>(.00)</td><td>.004</td><td>.07</td><td>(.03)</td><td>(.000)</td><td>2E-05</td><td>.024</td><td>(.05)</td><td></td></tr><tr><td>C</td><td></td><td>.002</td><td>.68</td><td></td><td></td><td>.001</td><td>.89</td><td></td><td></td><td>.002</td><td>.795</td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>28.2</td><td></td><td></td><td></td><td>9.34</td><td></td><td></td><td></td><td>22.3</td><td></td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.307</td><td></td><td></td><td></td><td>.394</td><td></td><td></td><td></td><td>.282</td><td></td><td></td><td></td></tr><tr><td rowspan="12">Economic crisis</td><td>ECT</td><td></td><td>-.670</td><td>.00</td><td></td><td></td><td>-.239</td><td>.00</td><td></td><td></td><td>-.603</td><td>.000</td><td></td><td></td></tr><tr><td>ECOC(-1)</td><td></td><td>.124</td><td>.00</td><td>23.6</td><td></td><td>-.136</td><td>.00</td><td>1.24</td><td></td><td>.060</td><td>.144</td><td>10.0</td><td></td></tr><tr><td>ECOC(-2)</td><td></td><td>.124</td><td>.00</td><td>(.00)</td><td></td><td>-.096</td><td>.03</td><td>(.53)</td><td></td><td>.119</td><td>.001</td><td>(.00)</td><td></td></tr><tr><td>FINC(-1)</td><td>-.679</td><td>.169</td><td>.00</td><td>14.8</td><td>-.290</td><td>.969</td><td>.00</td><td>84.4</td><td>-.561</td><td>-.375</td><td>.000</td><td>31.5</td><td></td></tr><tr><td>FINC(-2)</td><td>(.00)</td><td>.051</td><td>.24</td><td>(.00)</td><td>(.00)</td><td>.493</td><td>.00</td><td>(.00)</td><td>(.000)</td><td>-.248</td><td>.000</td><td>(.00)</td><td></td></tr><tr><td>INVEST(-1)</td><td>-.693</td><td>-.027</td><td>.00</td><td>16.2</td><td>-.650</td><td>-.097</td><td>.00</td><td>57.8</td><td>-.700</td><td>-.009</td><td>.267</td><td>1.27</td><td></td></tr><tr><td>INVEST(-2)</td><td>(.00)</td><td>-.009</td><td>.17</td><td>(.00)</td><td>(.00)</td><td>-.031</td><td>.02</td><td>(.00)</td><td>(.000)</td><td>-.002</td><td>.795</td><td>(.52)</td><td></td></tr><tr><td>CACCT(-1)</td><td>-.700</td><td>-.010</td><td>.06</td><td>3.56</td><td></td><td></td><td></td><td></td><td>5.32</td><td>-.696</td><td>-.009</td><td>.169</td><td>5.00</td><td></td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>.001</td><td>.75</td><td>(.16)</td><td></td><td></td><td></td><td></td><td>(.06)</td><td>(.000)</td><td>-.012</td><td>.061</td><td>(.08)</td><td></td></tr><tr><td>DCG(-1)</td><td>-.694</td><td>-.090</td><td>.12</td><td>3.44</td><td>-.645</td><td>.377</td><td>.00</td><td>18.6</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>.018</td><td>.75</td><td>(.17)</td><td>(.00)</td><td>.254</td><td>.00</td><td>(.00)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>C</td><td></td><td>-.005</td><td>.60</td><td></td><td></td><td>-.026</td><td>.14</td><td></td><td></td><td>.005</td><td>.715</td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>8.90</td><td></td><td></td><td></td><td>3.74</td><td></td><td></td><td></td><td>10.3</td><td></td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.317</td><td></td><td></td><td></td><td>.198</td><td></td><td></td><td></td><td>.308</td><td></td><td></td><td></td></tr><tr><td rowspan="12"></td><td rowspan="12"></td><td colspan="4">Bank</td><td colspan="4">Market</td><td colspan="4"></td></tr><tr><td></td><td>LTIE</td><td>coef</td><td>Prob</td><td>Wald</td><td>LTIE</td><td>coef</td><td>Prob</td><td>Wald</td><td>LTIE</td><td>coef</td><td>Prob</td><td>Wald</td></tr><tr><td>ECT</td><td></td><td>.043</td><td>.000</td><td></td><td></td><td>-.080</td><td>.001</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FINC(-1)</td><td></td><td>-.631</td><td>.000</td><td>270.</td><td></td><td>-.515</td><td>.000</td><td>150.</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FINC(-2)</td><td></td><td>-.274</td><td>.000</td><td>(.000)</td><td></td><td>-.237</td><td>.000</td><td>(.000)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(ECOC(-1)</td><td>-.377</td><td>-.057</td><td>.003</td><td>10.6</td><td>-.800</td><td>-.005</td><td>.980</td><td>1.04</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(ECOC(-2)</td><td>(.000)</td><td>-.037</td><td>.058</td><td>(.004)</td><td>(.000)</td><td>-.020</td><td>.316</td><td>(.592)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(FL(-1)</td><td>-.928</td><td>-.080</td><td>.001</td><td>12.5</td><td>-.970</td><td>-.001</td><td>.916</td><td>2.22</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(FL(-2)</td><td>(.000)</td><td>.047</td><td>.066</td><td>(.001)</td><td>(.000)</td><td>.027</td><td>.138</td><td>(.329)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GDPG(-1)</td><td>-.935</td><td>-.003</td><td>.339</td><td>.921</td><td>-.932</td><td>.001</td><td>.571</td><td>1.01</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>GDPG(-2)</td><td>(.000)</td><td>-.009</td><td>.764</td><td>(.630)</td><td>(.000)</td><td>-.002</td><td>.540</td><td>(.602)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TOTC(-1)</td><td>-.006</td><td>.366</td><td>.002</td><td>13.6</td><td>.023</td><td>-.677</td><td>.000</td><td>17.7</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TOTC(-2)</td><td>(.000)</td><td>.306</td><td>.000</td><td>(.001)</td><td>(.000)</td><td>-.432</td><td>.000</td><td>(.000)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>REER(-1)</td><td>-.895</td><td>.001</td><td>.040</td><td>12.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>REER(-2)</td><td>(.000)</td><td>.002</td><td>.027</td><td>(.002)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(RIR(-1)</td><td>-.350</td><td>1E-5</td><td>.523</td><td>1.06</td><td>-.824</td><td>-5E-5</td><td>.006</td><td>12.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(RIR(-2)</td><td>(.000)</td><td>1E-5</td><td>.305</td><td>(.588)</td><td>(.000)</td><td>2E-5</td><td>.176</td><td>(.001)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>C</td><td></td><td>.002</td><td>.760</td><td></td><td></td><td>.004</td><td>.633</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>28.9</td><td></td><td></td><td></td><td>20.9</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>R-squared</td><td></td><td>.323</td><td></td><td></td><td></td><td>.298</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="12">Economic crisis</td><td>ECT</td><td></td><td>-.510</td><td>.000</td><td></td><td></td><td>-.247</td><td>.000</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ECOC(-1)</td><td></td><td>.033</td><td>.478</td><td>4.04</td><td></td><td>-.065</td><td>.113</td><td>2.72</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ECOC(-2)</td><td></td><td>.083</td><td>.047</td><td>(.132)</td><td></td><td>-.039</td><td>.302</td><td>(.256)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FINC(-1)</td><td>-.437</td><td>.726</td><td>.000</td><td>89.3</td><td>-.089</td><td>.623</td><td>.000</td><td>54.4</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FINC(-2)</td><td>(.000)</td><td>.374</td><td>.000</td><td>(.000)</td><td>(.000)</td><td>.189</td><td>.009</td><td>(.000)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>INVEST(-1)</td><td>-.695</td><td>-.046</td><td>.000</td><td>18.5</td><td>-.627</td><td>-.004</td><td>.556</td><td>.471</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>INVEST(-2)</td><td>(.000)</td><td>-.011</td><td>.305</td><td>(.000)</td><td>(.000)</td><td>-.002</td><td>.728</td><td>(.790)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CACCT(-1)</td><td>-.711</td><td>-.025</td><td>.002</td><td>9.08</td><td>-.629</td><td>.019</td><td>.005</td><td>7.94</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CACCT(-2)</td><td>(.000)</td><td>-.002</td><td>.975</td><td>(.010)</td><td>(.000)</td><td>-.009</td><td>.900</td><td>(.018)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>DCG(-1)</td><td>-.721</td><td>.147</td><td>.167</td><td>2.32</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>DCG(-2)</td><td>(.000)</td><td>.009</td><td>.925</td><td>(.312)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>C</td><td></td><td>-.004</td><td>.795</td><td></td><td></td><td>.013</td><td>.420</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>8.60</td><td></td><td></td><td></td><td>10.4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.268</td><td></td><td></td><td></td><td>.148</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Values in parentheses correspond to *p*-values.

systems, it is negative, but not statistically significant, suggesting no short-run effect. The financial crisis appears to increase the likelihood of economic crises in both the short and long term, especially for emergent countries consistently to hypothesis 1.
<figure><img src="image_26.png" /></figure>

A: Full sample

<figure><img src="image_27.png" /></figure>

B: Developed

<figure><img src="image_28.png" /></figure>

C: Emergent

<figure><img src="image_29.png" /><figcaption>Figure 1. Impulses response function: financial sector.</figcaption></figure>

The findings presented in Figure 1 and the subsequent discussion provide valuable insights into the persistence and dynamics of financial shocks and economic shocks across different types of economies. It is evident from Figure 1 that financial shock, on average, are not highly persistent and tend to last
<figure><img src="image_30.png" /></figure>

D. Bank-based system

<figure><img src="image_31.png" /></figure>

E. Market-based system

<figure><img src="image_32.png" /><figcaption>**Figure 1.** Continued.</figcaption></figure>

around 3 years. This observation is consistent with existing literature that recognizes the cyclical nature of financial crises (Reinhart & Rogoff, 2009). Financial crises often involve acute disruptions followed by recovery periods. Interestingly, an increase in the likelihood of an economic shock significantly reduces the likelihood of a financial fragility for the next 5 years in the full sample, emergent countries, and bank-based systems. This implies that adverse economic conditions prompt cautious behavior, and this memory effect persists for 5 years before diminishing in the sixth year. This aligns with the literature on the impact of economic conditions on risk aversion and financial decision-making (Malmendier & Nagel, 2011). This suggests that economic shocks have a prolonged influence on financial behavior. This delay suggests a time lag in the transmission of economic shocks to the financial sphere, indicating long-term effects. This resonates with studies highlighting the delayed and lasting impact of economic downturns on the financial sector (Reinhart & Rogoff, 2009).

Furthermore, our findings reveal that the effect of a currency shock on financial sector is not only persistent but also exacerbates over time in bank-based systems. This revelation is an important contribution to the literature in line with research emphasizing the vulnerability of banking systems to external shocks, especially in economies closely connected to the external environment (Lestano et al., 2003). Conversely, the real interest rate emerges as the most significant destabilizing factor in market-based economies in line with the literature on the sensitivity of market-based financial systems to interest rate movements (Qin & Luo, 2014). High-interest rates can impact borrowing costs and financial stability

Specifically, the depreciation of the exchange rate significantly and enduringly increases the likelihood of a financial vulnerability in bank-based economies that are closely connected to the external environment. Other factors, such as capital account liberalization, economic growth, terms of trade, and the
<figure><img src="image_33.png" /></figure>

A. Full sample

B. Developed

Response to Cholesky One S.D. (d.f. adjusted) Innovations ± 2 S.E.

Response of ECOC to ECOC

<figure><img src="image_34.png" /></figure>

Response of ECOC to INVEST

<figure><img src="image_35.png" /></figure>

Response of ECOC to DCG

<figure><img src="image_36.png" /></figure>

Response to Cholesky One S.D. (d.f. adjusted) Innovations ± 2 S.E.

Response of ECOC to ECOC

<figure><img src="image_37.png" /></figure>

Response of ECOC to INVEST

<figure><img src="image_38.png" /></figure>

Response of ECOC to DCG

<figure><img src="image_39.png" /></figure>

Response of ECOC to FINC

<figure><img src="image_40.png" /></figure>

Response of ECOC to CACCT

<figure><img src="image_41.png" /></figure>

Response of ECOC to FINC

<figure><img src="image_42.png" /></figure>

Response of ECOC to CACCT

<figure><img src="image_43.png" /><figcaption>**Figure 2.** Impulse response functions: economic situation.</figcaption></figure>

economic growth rate, exhibit similar effects across all countries and do not distinctly influence the stability of the financial sector. These findings contribute to our understanding of universal determinants of financial stability. The non-distinct influence of certain factors across countries aligns with studies that emphasize the importance of global and systemic factors in shaping financial stability, transcending specific economic structures (Claessens et al., 2005).

Figure 2 illustrates that the economic shock exhibits greater persistence, lasting for more than 4 years compared to the 3-year duration of financial one. This aligns with the understanding that economic downturns can have long-lasting effects on the real economy emphasizing the lingering impact of economic crises on growth and development (Reinhart & Rogoff, 2009). Moreover, the impact of a shock in the financial sphere on the economic sphere is immediate, positive, significant, and enduring for at least 5 years, with more pronounced importance observed in emergent markets. This finding is consistent with research indicating that financial disruptions can quickly spill over into the real economy (Kaminsky & Reinhart, 1999). The greater importance observed in emergent markets underscores the vulnerability of developing economies to financial shocks, as documented in studies highlighting the impact of financial instability on emerging markets (Frankel & Saravelos, 2012). This outcome implies that, generally, economic crises are preceded by financial vulnerabilities and fluctuations. This supports the literature on the financial amplification mechanism, where disruptions in the financial sector can exacerbate economic downturns (Bernanke et al., 1999). However, it is noteworthy that a financial shock does not necessarily
<figure><img src="image_44.png" /></figure>

<figure><img src="image_45.png" /><figcaption>Figure 2. Continued.</figcaption></figure>

lead to a subsequent deterioration of economic conditions; instead, it can be self-fulfilling. This recognition echoes the concept of confidence-driven recessions and the role of expectations in economic dynamics (Minsky, 1992).

Furthermore, the effect of investment on the real economy only becomes positive and significant in the long term, specifically from the fifth year in the full sample, and is never significant for the market-based system. This finding suggests that the impact of investment decisions on economic growth
<figure><img src="image_46.png" /></figure>

may take time to materialize in line with the literature on the time lags in the transmission of investment effects on economic activity (Easterly & Rebelo, 1993). Although the volatility of investment is transmit- ted to economic volatility from the fourth year in developed countries, this effect becomes more dis- tinctly significant and immediate, starting from the second year. This observation supports the notion that investment fluctuations can contribute to economic instability (Eberly & Krishnamurthy, 2014).

In summary, the study's findings contribute to the literature by providing empirical evidence on the persistence of economic shocks, the immediate impact of financial shocks on the real economy, and the time dynamics of investment effects. These insights enhance our understanding of the complex interac- tions between the financial and real sectors, offering implications for policymakers in managing and mitigating the impact of shocks on economic stability. The discussion underscores the importance of considering temporal aspects and system-specific characteristics in analyzing the dynamics of economic and financial interactions.

The vulnerability decomposition analysis presented in Table 8 offers insights into the short-term and long-term determinants of financial and economic vulnerabilities across different subsamples. Our analy- sis reveals that in the short term, the variance of the probability of a financial crisis is primarily influ- enced by its own evolution across all subsamples. This observation is consistent with the idea of self-reinforcing dynamics in financial markets, where recent developments and sentiments play a crucial role. Conversely, in the long term, more than half of this variance in the bank-based system and over a quarter in the full sample is explained by fluctuations in the exchange rate, and to a lesser extent by changes in the terms of trade and the vulnerabilities of economic fundamentals that determine the probability of an economic crisis. This finding aligns with research emphasizing the role of external fac- tors in shaping financial vulnerabilities (Lestano et al., 2003). Changes in the terms of trade and vulner- abilities of economic fundamentals contributing to the long-term variance in financial vulnerability support the notion that both external and internal factors contribute to the sustained vulnerability of financial systems (Reinhart & Rogoff, 2009).

Regarding economic vulnerability, our findings indicate that it predominantly depends on its own evo- lution and on financial stability for all subsamples. This indication is consistent with the literature on the self-reinforcing nature of economic downturns and the persistence of economic challenges (Reinhart & Rogoff, 2009). The finding that financial stability influences economic vulnerability aligns with the concept that disruptions in the financial sector can have direct and immediate consequences for the real econ- omy, especially in times of crisis (Bernanke et al., 1999). Notably, the level of investment plays a more significant role in developed countries compared to emergent nations, and in bank-based economies relative to market-based systems. This observation suggests that the impact of investment decisions on economic vulnerability may vary across different economic structures (Easterly & Rebelo, 1993). The results highlight the importance of financial stability and investment dynamics in shaping economic vulnerabil- ity, underscoring the need for coordinated policies that address both financial and real sector challenges.

The vulnerability decomposition analysis provides valuable insights into the short-term and long-term determinants of financial and economic vulnerabilities across different subsamples. The findings align with existing literature on the complex interplay between financial and real sectors, the role of external factors in financial stability, and the varied impact of investment on economic vulnerability across differ- ent economic structures. These insights contribute to a more nuanced understanding of the factors driv- ing vulnerability and can inform policy decisions aimed at enhancing both financial and economic resilience.

The findings presented in Tables 9(A,B) provide insights into the causal relationships among various economic and financial indicators across different subsamples. Table 9(A) highlights that a financial crisis can be instigated by an economic crisis across all subsamples consistent with the literature that high- lights the linkages between economic downturns and financial instability (Reinhart & Rogoff, 2009). The result supports the idea that economic crises can lead to financial crises through channels such as reduced creditworthiness, increased default rates, and disruptions in financial markets (Bernanke et al., 1999). Similarly, inappropriate capital account liberalization, a deterioration of terms of trade, and an increase in the real interest rate cause a financial crisis in the full sample and market-based systems. The identification of specific indicators causing financial crises aligns with existing literature on the role of capital account liberalization, terms of trade, and interest rates in financial instability, as noted by various
<figure><img src="image_47.png" /><figcaption>**Table 8.** Variance decomposition.</figcaption></figure>

<table><thead><tr><th rowspan="3">Period</th><th colspan="10">Financial crisis</th></tr><tr><th colspan="5">Full</th><th colspan="4">Developed</th><th colspan="4">Emergent</th></tr><tr><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>REER</th><th>RIR</th><th>FINC</th><th>ECOC</th><th>GDPG</th><th>RIR</th><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>RIR</th></tr></thead><tbody><tr><td>1</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>2</td><td>97.2</td><td>.747</td><td>.219</td><td>.077</td><td>.504</td><td>1.10</td><td>.103</td><td>99.3</td><td>.000</td><td>.050</td><td>.625</td><td>97.5</td><td>.127</td><td>.710</td><td>.004</td><td>.479</td><td>.017</td></tr><tr><td>3</td><td>91.5</td><td>1.14</td><td>.254</td><td>.207</td><td>.843</td><td>5.76</td><td>.193</td><td>98.7</td><td>.215</td><td>.401</td><td>.623</td><td>96.2</td><td>1.77</td><td>.727</td><td>.121</td><td>.506</td><td>.587</td></tr><tr><td>4</td><td>86.9</td><td>1.00</td><td>.200</td><td>.408</td><td>1.46</td><td>9.81</td><td>.159</td><td>98.5</td><td>.216</td><td>.642</td><td>.630</td><td>95.8</td><td>2.05</td><td>.734</td><td>.144</td><td>.518</td><td>.692</td></tr><tr><td>5</td><td>82.5</td><td>.962</td><td>.172</td><td>.463</td><td>1.97</td><td>13.7</td><td>.136</td><td>98.4</td><td>.245</td><td>.703</td><td>.631</td><td>95.7</td><td>2.16</td><td>.744</td><td>.148</td><td>.519</td><td>.692</td></tr><tr><td>6</td><td>78.5</td><td>.930</td><td>.151</td><td>.525</td><td>2.45</td><td>17.2</td><td>.117</td><td>98.3</td><td>.317</td><td>.723</td><td>.642</td><td>95.6</td><td>2.21</td><td>.755</td><td>.148</td><td>.521</td><td>.692</td></tr><tr><td>7</td><td>75.2</td><td>.900</td><td>.134</td><td>.586</td><td>2.77</td><td>20.2</td><td>.101</td><td>98.2</td><td>.391</td><td>.730</td><td>.654</td><td>95.6</td><td>2.22</td><td>.765</td><td>.148</td><td>.521</td><td>.692</td></tr><tr><td>8</td><td>72.4</td><td>.866</td><td>.122</td><td>.627</td><td>3.06</td><td>22.7</td><td>.089</td><td>98.1</td><td>.449</td><td>.734</td><td>.669</td><td>95.6</td><td>2.22</td><td>.775</td><td>.149</td><td>.521</td><td>.692</td></tr><tr><td>9</td><td>70.1</td><td>.837</td><td>.112</td><td>.661</td><td>3.33</td><td>24.7</td><td>.079</td><td>98.0</td><td>.493</td><td>.739</td><td>.682</td><td>95.6</td><td>2.22</td><td>.783</td><td>.149</td><td>.521</td><td>.692</td></tr><tr><td>10</td><td>68.2</td><td>.816</td><td>.103</td><td>.691</td><td>3.54</td><td>26.5</td><td>.071</td><td>98.0</td><td>.527</td><td>.743</td><td>.694</td><td>95.6</td><td>2.22</td><td>.791</td><td>.149</td><td>.521</td><td>.692</td></tr><tr><th rowspan="3">Period</th><th colspan="10">Bank</th></tr><tr><th colspan="5">Full</th><th colspan="4">Market</th><th colspan="4">Emergent</th></tr><tr><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>REER</th><th>RIR</th><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>RIR</th><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th></tr><tr><td>1</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>2</td><td>94.5</td><td>1.31</td><td>1.57</td><td>.027</td><td>.241</td><td>2.32</td><td>.010</td><td>98.4</td><td>.702</td><td>.166</td><td>.142</td><td>.464</td><td>.059</td><td>.059</td><td>.059</td><td>.059</td><td>.059</td></tr><tr><td>3</td><td>89.0</td><td>1.97</td><td>1.48</td><td>.028</td><td>.377</td><td>7.04</td><td>.012</td><td>96.0</td><td>1.47</td><td>.217</td><td>.265</td><td>.473</td><td>1.47</td><td>.147</td><td>.147</td><td>.147</td><td>.147</td></tr><tr><td>4</td><td>82.1</td><td>2.04</td><td>1.38</td><td>.028</td><td>.684</td><td>13.5</td><td>.146</td><td>95.3</td><td>1.82</td><td>.294</td><td>.266</td><td>.474</td><td>1.76</td><td>.176</td><td>.176</td><td>.176</td><td>.176</td></tr><tr><td>5</td><td>74.0</td><td>1.88</td><td>1.27</td><td>.030</td><td>1.12</td><td>21.3</td><td>.299</td><td>95.2</td><td>1.91</td><td>.365</td><td>.267</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><td>6</td><td>64.9</td><td>1.65</td><td>1.14</td><td>.028</td><td>1.66</td><td>30.0</td><td>.478</td><td>95.1</td><td>1.92</td><td>.431</td><td>.275</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><td>7</td><td>55.5</td><td>1.40</td><td>.999</td><td>.024</td><td>2.23</td><td>39.0</td><td>.668</td><td>95.0</td><td>1.92</td><td>.488</td><td>.280</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><td>8</td><td>46.2</td><td>1.17</td><td>.841</td><td>.021</td><td>2.80</td><td>48.0</td><td>.855</td><td>95.0</td><td>1.92</td><td>.538</td><td>.283</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><td>9</td><td>37.5</td><td>.947</td><td>.687</td><td>.019</td><td>3.36</td><td>56.3</td><td>1.02</td><td>94.9</td><td>1.92</td><td>.583</td><td>.284</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><td>10</td><td>29.8</td><td>.749</td><td>.547</td><td>.019</td><td>3.86</td><td>63.7</td><td>1.18</td><td>94.9</td><td>1.92</td><td>.623</td><td>.284</td><td>.473</td><td>1.77</td><td>.177</td><td>.177</td><td>.177</td><td>.177</td></tr><tr><th rowspan="3">Period</th><th colspan="10">Economic crisis</th></tr><tr><th colspan="5">Full</th><th colspan="4">Developed</th><th colspan="4">Emergent</th></tr><tr><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th><th>DCG</th><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th><th>DCG</th><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th></tr><tr><td>1</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>2</td><td>96.9</td><td>1.80</td><td>.887</td><td>.163</td><td>.217</td><td>94.7</td><td>2.17</td><td>3.04</td><td>.062</td><td>.019</td><td>97.7</td><td>1.96</td><td>.083</td><td>.159</td><td>.159</td><td>.159</td><td>.159</td></tr><tr><td>3</td><td>95.7</td><td>2.53</td><td>1.09</td><td>.325</td><td>.263</td><td>93.4</td><td>2.85</td><td>3.51</td><td>.104</td><td>.024</td><td>96.4</td><td>2.97</td><td>.252</td><td>.343</td><td>.343</td><td>.343</td><td>.343</td></tr><tr><td>4</td><td>95.5</td><td>2.69</td><td>1.12</td><td>.381</td><td>.263</td><td>93.3</td><td>2.98</td><td>3.51</td><td>.107</td><td>.031</td><td>95.7</td><td>3.09</td><td>.743</td><td>.421</td><td>.421</td><td>.421</td><td>.421</td></tr><tr><td>5</td><td>95.5</td><td>2.69</td><td>1.12</td><td>.397</td><td>.267</td><td>93.1</td><td>2.97</td><td>3.77</td><td>.11</td><td>.033</td><td>95.1</td><td>3.07</td><td>1.35</td><td>.445</td><td>.445</td><td>.445</td><td>.445</td></tr><tr><td>6</td><td>95.5</td><td>2.69</td><td>1.12</td><td>.406</td><td>.268</td><td>92.6</td><td>3.01</td><td>4.15</td><td>.133</td><td>.034</td><td>94.5</td><td>3.06</td><td>1.94</td><td>.450</td><td>.450</td><td>.450</td><td>.450</td></tr><tr><td>7</td><td>95.4</td><td>2.69</td><td>1.12</td><td>.413</td><td>.268</td><td>92.2</td><td>3.05</td><td>4.46</td><td>.165</td><td>.034</td><td>93.9</td><td>3.07</td><td>2.48</td><td>.449</td><td>.449</td><td>.449</td><td>.449</td></tr><tr><td>8</td><td>95.4</td><td>2.69</td><td>1.12</td><td>.421</td><td>.268</td><td>92.0</td><td>3.07</td><td>4.66</td><td>.203</td><td>.033</td><td>93.5</td><td>3.08</td><td>2.96</td><td>.446</td><td>.446</td><td>.446</td><td>.446</td></tr><tr><td>9</td><td>95.4</td><td>2.69</td><td>1.13</td><td>.429</td><td>.268</td><td>91.8</td><td>3.07</td><td>4.80</td><td>.247</td><td>.033</td><td>93.0</td><td>3.09</td><td>3.40</td><td>.445</td><td>.445</td><td>.445</td><td>.445</td></tr><tr><td>10</td><td>95.4</td><td>2.69</td><td>1.13</td><td>.437</td><td>.268</td><td>91.6</td><td>3.07</td><td>4.92</td><td>.297</td><td>.033</td><td>92.6</td><td>3.09</td><td>3.80</td><td>.447</td><td>.447</td><td>.447</td><td>.447</td></tr><tr><th rowspan="3">Period</th><th colspan="10">Bank</th></tr><tr><th colspan="5">Full</th><th colspan="4">Market</th><th colspan="4">Emergent</th></tr><tr><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th><th>DCG</th><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th><th>DCG</th><th>ECOC</th><th>FINC</th><th>INVEST</th><th>CACCT</th></tr><tr><td>1</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>100</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>2</td><td>96.3</td><td>2.43</td><td>.458</td><td>.509</td><td>.209</td><td>98.1</td><td>1.45</td><td>.000</td><td>.000</td><td>.000</td><td>98.1</td><td>1.45</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td>3</td><td>95.2</td><td>3.23</td><td>.448</td><td>.678</td><td>.372</td><td>97.7</td><td>1.86</td><td>.003</td><td>.003</td><td>.003</td><td>97.7</td><td>1.86</td><td>.003</td><td>.003</td><td>.003</td><td>.003</td><td>.003</td></tr><tr><td>4</td><td>94.8</td><td>3.37</td><td>.688</td><td>.702</td><td>.375</td><td>97.6</td><td>1.89</td><td>.003</td><td>.003</td><td>.003</td><td>97.6</td><td>1.89</td><td>.003</td><td>.003</td><td>.003</td><td>.003</td><td>.003</td></tr><tr><td>5</td><td>94.4</td><td>3.36</td><td>1.07</td><td>.699</td><td>.373</td><td>97.6</td><td>1.89</td><td>.005</td><td>.005</td><td>.005</td><td>97.6</td><td>1.89</td><td>.005</td><td>.005</td><td>.005</td><td>.005</td><td>.005</td></tr><tr><td>6</td><td>94.1</td><td>3.36</td><td>1.43</td><td>.704</td><td>.372</td><td>97.5</td><td>1.89</td><td>.007</td><td>.007</td><td>.007</td><td>97.5</td><td>1.89</td><td>.007</td><td>.007</td><td>.007</td><td>.007</td><td>.007</td></tr><tr><td>7</td><td>93.7</td><td>3.37</td><td>1.74</td><td>.717</td><td>.370</td><td>97.5</td><td>1.89</td><td>.008</td><td>.008</td><td>.008</td><td>97.5</td><td>1.89</td><td>.008</td><td>.008</td><td>.008</td><td>.008</td><td>.008</td></tr><tr><td>8</td><td>93.5</td><td>3.37</td><td>2.00</td><td>.736</td><td>.369</td><td>97.5</td><td>1.89</td><td>.009</td><td>.009</td><td>.009</td><td>97.5</td><td>1.89</td><td>.009</td><td>.009</td><td>.009</td><td>.009</td><td>.009</td></tr><tr><td>9</td><td>93.2</td><td>3.36</td><td>2.22</td><td>.762</td><td>.368</td><td>97.5</td><td>1.89</td><td>.010</td><td>.010</td><td>.010</td><td>97.5</td><td>1.89</td><td>.010</td><td>.010</td><td>.010</td><td>.010</td><td>.010</td></tr><tr><td>10</td><td>93.0</td><td>3.36</td><td>2.42</td><td>.795</td><td>.368</td><td>97.4</td><td>1.89</td><td>.011</td><td>.011</td><td>.011</td><td>97.4</td><td>1.89</td><td>.011</td><td>.011</td><td>.011</td><td>.011</td><td>.011</td></tr></tbody></table>

studies (Hamdaoui et al., 2022; Frankel & Saravelos, 2012). The significance of inappropriate capital account liberalization, a deterioration of terms of trade, and an increase in the real interest rate as factors causing a financial crisis in the full sample and market-based systems aligns with research highlighting the role of external factors and interest rate movements in financial stability (Lestano et al., 2003; Qin & Luo, 2014). However, the real interest rate does not significantly cause a financial crisis in emergent and bank-system economies. This may suggest that interest rate dynamics have a varied impact on financial stability in different economic contexts. Additionally, the economic growth rate is not a significant factor causing a financial crisis, while real exchange depreciation triggers financial vulnerabilities in the full sample and emergent countries. The finding contrasts with some literature that emphasizes the importance of economic growth in mitigating financial instability (Levine & Zervos, 1998). This result may indicate that other factors play a more prominent role in triggering financial crises such as the real exchange depreciation consistent with the literature highlighting the impact of currency fluctuations on financial
<table><caption>Table 9. Granger causality tests.</caption><thead><tr><th></th><th>Variables</th><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>REER</th><th>RIR</th></tr></thead><tbody><tr><td rowspan="6">Full sample</td><td>FINC</td><td></td><td>(7E-09)</td><td>(.029)</td><td>(2E-17)</td><td>(3.E-15)</td><td>(.047)</td><td>(6E-06)</td></tr><tr><td>ECOC</td><td>(8E-7)</td><td></td><td>(.011)</td><td>(2E-83)</td><td>(9E-06)</td><td>(.125)</td><td>(.254)</td></tr><tr><td>FL</td><td>(.000)</td><td>(.731)</td><td></td><td>(.002)</td><td>(.0495)</td><td>(.158)</td><td>(.064)</td></tr><tr><td>GDPG</td><td>(.870)</td><td>(5E-15)</td><td>(.068)</td><td></td><td></td><td>(.005)</td><td>(.911)</td></tr><tr><td>TOTC</td><td>(.033)</td><td>(.047)</td><td>(.056)</td><td>(1.E-21)</td><td>(3E-7)</td><td>(.000)</td><td>(.012)</td></tr><tr><td>REER</td><td>(.000)</td><td>(.366)</td><td>(.416)</td><td>(6.E-08)</td><td>(3E-5)</td><td></td><td>(.130)</td></tr><tr><td rowspan="4">Developed</td><td>RIR</td><td>(.029)</td><td>(.557)</td><td>(.785)</td><td>(.1507)</td><td>(.0428)</td><td>(.008)</td><td></td></tr><tr><td>FINC</td><td>FINC</td><td>(3E-5)</td><td>ECOC</td><td>GDPG</td><td>RIR</td><td></td><td></td></tr><tr><td>ECOC</td><td>(3E-5)</td><td></td><td>(7.E-12)</td><td>(.211)</td><td></td><td></td><td></td></tr><tr><td>GDPG</td><td>(.557)</td><td>(2E-13)</td><td>(7E-33)</td><td>(.386)</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Emergent</td><td>RIR</td><td>(.359)</td><td>(.002)</td><td>(.010)</td><td></td><td></td><td></td><td></td></tr><tr><td>FINC</td><td>FINC</td><td>ECOC</td><td>FL</td><td>GDPG</td><td>TOTC</td><td>RIR</td><td></td></tr><tr><td>ECOC</td><td>(.001)</td><td>(4E-5)</td><td>(.064)</td><td>(3E-10)</td><td>(9E-13)</td><td>(3E-5)</td><td></td></tr><tr><td>FL</td><td>(.014)</td><td>(.793)</td><td>(.001)</td><td>(5E-53)</td><td>(.001)</td><td>(.285)</td><td></td></tr><tr><td rowspan="6">Bank</td><td>GDPG</td><td>(.478)</td><td>(1E-7)</td><td>(.344)</td><td>(.497)</td><td>(.034)</td><td>(.257)</td><td></td></tr><tr><td>TOTC</td><td>(.025)</td><td>(.620)</td><td>(.240)</td><td>(5E-16)</td><td>(.000)</td><td>(.815)</td><td></td></tr><tr><td>RIR</td><td>(3.07)</td><td>(.527)</td><td>(.865)</td><td>(.289)</td><td>(0.135)</td><td></td><td></td></tr><tr><td>FINC</td><td>FINC</td><td>ECOC</td><td>FL</td><td>GDPG</td><td>TOTC</td><td>REER</td><td>RIR</td></tr><tr><td>ECOC</td><td>(.000)</td><td>(3E-5)</td><td>(.105)</td><td>(1E-12)</td><td>(2.E-10)</td><td>(.212)</td><td>(6E-5)</td></tr><tr><td>FL</td><td>(.001)</td><td>(.949)</td><td>(.308)</td><td>(1E-37)</td><td>(.003)</td><td>(.401)</td><td>(.485)</td></tr><tr><td rowspan="6">Market</td><td>GDPG</td><td>(.500)</td><td>(8E-5)</td><td>(.028)</td><td>(7.E-05)</td><td>(.125)</td><td>(.063)</td><td>(.525)</td></tr><tr><td>TOTC</td><td>(.466)</td><td>(.683)</td><td>(.095)</td><td>(3E-14)</td><td>(3E-6)</td><td>(.005)</td><td>(.458)</td></tr><tr><td>REER</td><td>(.004)</td><td>(.771)</td><td>(.116)</td><td>(6E-5)</td><td>(.015)</td><td></td><td></td></tr><tr><td>RIR</td><td>(.773)</td><td>(.678)</td><td>(.950)</td><td>(.007)</td><td>(.000)</td><td>(1.E-07)</td><td></td></tr><tr><td>FINC</td><td>FINC</td><td>ECOC</td><td>FL</td><td>GDPG</td><td>TOTC</td><td>RIR</td><td></td></tr><tr><td>ECOC</td><td>(.004)</td><td>(.000)</td><td>(.741)</td><td>(.000)</td><td>(4.E-6)</td><td>(.004)</td><td></td></tr><tr><td rowspan="6">Full sample</td><td>FINC</td><td></td><td>(8E-07)</td><td>(2E-24)</td><td>(.000)</td><td>(.001)</td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>(7.E-9)</td><td>(7E-20)</td><td>(2E-12)</td><td>(.000)</td><td></td><td></td></tr><tr><td>FINC</td><td></td><td>(9.E-7)</td><td>(.271)</td><td>(2E-8)</td><td></td><td></td><td></td></tr><tr><td>INVEST</td><td></td><td>(.261)</td><td>(6E-5)</td><td>(2E-18)</td><td></td><td>(.872)</td><td></td></tr><tr><td>CACCT</td><td></td><td>(.024)</td><td>(.190)</td><td>(.000)</td><td>(.567)</td><td></td><td></td></tr><tr><td>DCG</td><td></td><td>(.024)</td><td>(.190)</td><td>(.000)</td><td>(.567)</td><td></td><td></td></tr><tr><td rowspan="6">Developed</td><td>ECOC</td><td></td><td>FINC</td><td>INVEST</td><td>CACCT</td><td>DCG</td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>(3E-5)</td><td>(2E-13)</td><td>(.003)</td><td>(.015)</td><td></td><td></td></tr><tr><td>FINC</td><td></td><td>(3E-5)</td><td>(.047)</td><td>(.003)</td><td>(.270)</td><td></td><td></td></tr><tr><td>INVEST</td><td></td><td>(1E-9)</td><td>(4E-8)</td><td>(.003)</td><td>(.368)</td><td></td><td></td></tr><tr><td>CACCT</td><td></td><td>(.289)</td><td>(.043)</td><td>(2E-7)</td><td>(.575)</td><td></td><td></td></tr><tr><td>DCG</td><td></td><td>(.921)</td><td>(.738)</td><td>(.293)</td><td>(.336)</td><td></td><td></td></tr><tr><td rowspan="4">Emergent</td><td>ECOC</td><td></td><td>FINC</td><td>INVEST</td><td>CACCT</td><td></td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>(.001)</td><td>(6E-13)</td><td>(.012)</td><td></td><td></td><td></td></tr><tr><td>FINC</td><td></td><td>(4E-5)</td><td>(.722)</td><td>(3E-13)</td><td>(3E-11)</td><td></td><td></td></tr><tr><td>INVEST</td><td></td><td>(.017)</td><td>(.722)</td><td>(3E-13)</td><td>(2E-7)</td><td></td><td></td></tr><tr><td rowspan="6">Bank</td><td>CACCT</td><td></td><td>(.316)</td><td>(.001)</td><td>(3E-10)</td><td></td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>FINC</td><td>INVEST</td><td>CACCT</td><td>DCG</td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>(.000)</td><td>(1E-15)</td><td>(.019)</td><td>(.006)</td><td></td><td></td></tr><tr><td>FINC</td><td></td><td>(3E-5)</td><td>(.875)</td><td>(7E-11)</td><td>(8E-9)</td><td>(4E-5)</td><td></td></tr><tr><td>INVEST</td><td></td><td>(.004)</td><td>(.875)</td><td>(7E-11)</td><td>(3E-6)</td><td>(.005)</td><td></td></tr><tr><td>CACCT</td><td></td><td>(.733)</td><td>(.216)</td><td>(1E-13)</td><td>(.642)</td><td></td><td></td></tr><tr><td></td><td>DCG</td><td></td><td>(.172)</td><td>(.633)</td><td>(.004)</td><td>.391(.676)</td><td></td><td></td></tr></tbody></table>

(Continued)
<figure><img src="image_48.png" /><figcaption>**Table 9. Continued.**</figcaption></figure>

<table><thead><tr><th colspan="8">9A: Financial crisis</th></tr><tr><th>Variables</th><th>FINC</th><th>ECOC</th><th>FL</th><th>GDPG</th><th>TOTC</th><th>REER</th><th>RIR</th></tr></thead><tbody><tr><td>Market</td><td>ECOC</td><td>FINC</td><td>INVEST</td><td>CACCT</td><td></td><td></td><td></td></tr><tr><td>ECOC</td><td></td><td>(.004)</td><td>(.536)</td><td>(.040)</td><td></td><td></td><td></td></tr><tr><td>FINC</td><td>(.000)</td><td></td><td>(.477)</td><td>(6E-6)</td><td></td><td></td><td></td></tr><tr><td>INVEST</td><td>(.985)</td><td>(.908)</td><td></td><td>(.325)</td><td></td><td></td><td></td></tr><tr><td>CACCT</td><td>(.048)</td><td>(9E-5)</td><td>(.527)</td><td></td><td></td><td></td><td></td></tr></tbody></table>

stability (Frankel & Saravelos, 2012). Moreover, it is observed that a financial crisis causes modifications in all its determinants, except for financial liberalization in the case of bank and market systems, real interest rates for developed countries, and real exchange rates for bank-based systems, as indicated by its significant effect presented in the first line. This observation suggests a feedback loop between the economic sphere and the financial sector in line with the concept of financial amplification, where disruptions in the financial sector can exacerbate economic challenges and vice versa (Bernanke et al., 1999). The specific cases where financial liberalization in the case of bank and market systems, real interest rates for developed countries, and real exchange rates for bank-based systems are not significantly affected by a financial crisis may indicate that certain factors are more resilient to the immediate impact of financial shocks. This suggests a causal relationship from the economic sphere to the financial sector for all economies.

Table 9(B) supports bidirectional causality between financial and economic crises for all subsamples consistent with hypothesis 3. This resonates with the literature emphasizing the feedback loops and interconnectedness between financial and real sectors (Reinhart & Rogoff, 2009). We also observe a two-way causal relationship between the economic crisis and investment, except for market-based economies. The two-way causal relationship supports the idea that economic downturns can lead to reduced investment, contributing to a further contraction in economic activity (Easterly & Rebelo, 1993). On the other hand, the current account balance does not cause an economic crisis, while the economic crisis leads to the deterioration of the current account for all types of countries. This suggests that external imbalances may be a consequence rather than a cause of economic crises in the studied economies. While there are significant causal relationships between different indicators at conventional thresholds, we do not detail them here due to paper length constraints. Despite the importance of these findings, further precision is needed since financial situations are represented by binary variables indicating the presence or absence of a crisis without emphasizing intermediate situations. Thus, the P-VECM allows for both short- and long-term studies. In the next part, we delve into the continuous variables measuring the probability of a financial crisis to explore the long-term interactions of our variables of interest. The shift to exploring continuous variables measuring the probability of a financial crisis in the long term using P-VECM reflects an effort to overcome the limitations of binary representations, allowing for a more detailed examination of long-term interactions.

In summary, the findings are in line with established theories and empirical evidence on the interconnectedness between economic and financial variables. The results emphasize the importance of considering bidirectional causality and feedback effects in understanding the dynamics of financial and economic crises. The shift towards exploring continuous variables in the long term reflects a methodological advancement to provide more detailed insights into the interactions among key variables.

### 3.3.2. Continuous analysis

Table 10 illustrating the outcomes of the simultaneous equations method utilizing continuous indicators to characterize economic and financial conditions, closely aligns with the earlier findings employing the same methodology. Notably, the persistence of the observation that an economic crisis does not exert a significant impact on explaining the occurrence of a financial crisis is retained, while conversely, a financial crisis significantly diminishes the likelihood of an economic crisis. Firstly, this resonates with studies such as those conducted by Dabrowski et al. (2016) who found that economic variables may not be strong predictors of financial crises. This consistency in results underscores the complex and multifaceted
<figure><img src="image_49.png" /><figcaption>**Table 10.** Simultaneous equation regression.</figcaption></figure>

<table><thead><tr><th colspan="6">Dependent variable: financial crisis/endogenous variable: Economic crisis</th><th colspan="6">Dependent variable: Economic crisis/endogenous variable: Financial crisis</th></tr><tr><th></th><th>Full sample</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th><th></th><th>Full sample</th><th>Developed</th><th>Emergent</th><th>Bank</th><th>Market</th></tr></thead><tbody><tr><td>PrEcoC</td><td>-.014<br>(.53)</td><td>-.008<br>(.69)</td><td>.037<br>(.27)</td><td>-.057<br>(.08)</td><td>-.006<br>(.78)</td><td>PrFinC</td><td>-.041<br>(.00)</td><td>-.048<br>(.15)</td><td>-.039<br>(.00)</td><td>-.057<br>(.00)</td><td>-.019<br>(.10)</td></tr><tr><td>FL</td><td>-.022<br>(.00)</td><td>-.014<br>(.00)</td><td>-.026<br>(.00)</td><td>-.025<br>(.00)</td><td>-.021<br>(.00)</td><td>FL</td><td>.002<br>(.00)</td><td>.003<br>(.74)</td><td>.002<br>(.00)</td><td>.002<br>(.00)</td><td>.003<br>(.00)</td></tr><tr><td>GDPG</td><td>-.011<br>(.00)</td><td>-.008<br>(.00)</td><td>-.011<br>(.00)</td><td>-.010<br>(.00)</td><td>-.012<br>(.00)</td><td>CPS</td><td>.006<br>(.00)</td><td>.005<br>(.00)</td><td>.006<br>(.00)</td><td>.008<br>(.00)</td><td>.007<br>(.00)</td></tr><tr><td>CACCT</td><td>-.004<br>(.00)</td><td>-.004<br>(.00)</td><td>-.005<br>(.00)</td><td>-.003<br>(.00)</td><td>-.004<br>(.00)</td><td>M2RES</td><td>-.001<br>(.00)</td><td>-.001<br>(.00)</td><td>-.001<br>(.00)</td><td>-.002<br>(.00)</td><td>-.002<br>(.00)</td></tr><tr><td>DCG</td><td>-.040<br>(.00)</td><td>-.013<br>(.06)</td><td>-.053<br>(.00)</td><td>-.031<br>(.00)</td><td>-.028<br>(.00)</td><td>INFL</td><td>.006<br>(.00)</td><td>.002<br>(.61)</td><td>.006<br>(.00)</td><td>.007<br>(.00)</td><td>.005<br>(.00)</td></tr><tr><td>CPSB</td><td></td><td></td><td></td><td></td><td></td><td>REER</td><td>.001<br>(.00)</td><td>-.007<br>(.37)</td><td>.001<br>(.00)</td><td>.004<br>(.03)</td><td>.003<br>(.47)</td></tr><tr><td>TOTC</td><td>.296<br>(.00)</td><td>.131<br>(.00)</td><td>.309<br>(.00)</td><td>.368<br>(.00)</td><td>.200<br>(.00)</td><td>PREG</td><td>-.001<br>(.56)</td><td>-.005<br>(.66)</td><td>-.001<br>(.48)</td><td>-.013<br>(.00)</td><td>-.017<br>(.00)</td></tr><tr><td>KFLOW</td><td>.001<br>(.00)</td><td>.001<br>(.00)</td><td>.001<br>(.00)</td><td>.001<br>(.00)</td><td>.001<br>(.00)</td><td>PR</td><td>-.001<br>(.00)</td><td>-.001<br>(.00)</td><td>-.002<br>(.00)</td><td>-.002<br>(.00)</td><td>-.001<br>(.00)</td></tr><tr><td>M2RES</td><td>.004<br>(.00)</td><td>.003<br>(.00)</td><td>.002<br>(.00)</td><td>-.002<br>(.90)</td><td>.006<br>(.00)</td><td>TRADE</td><td>-.002<br>(.00)</td><td>-.004<br>(.00)</td><td>-.002<br>(.00)</td><td>.001<br>(.00)</td><td>.001<br>(.00)</td></tr><tr><td>INFL</td><td>-.001<br>(.00)</td><td>.003<br>(.00)</td><td>-.003<br>(.00)</td><td>-.003<br>(.07)</td><td>-.002<br>(.00)</td><td>POPG</td><td>-.036<br>(.00)</td><td>-.030<br>(.00)</td><td>-.038<br>(.00)</td><td>-.040<br>(.00)</td><td>-.038<br>(.00)</td></tr><tr><td>REER</td><td>.006<br>(.00)</td><td>.002<br>(.00)</td><td>.006<br>(.00)</td><td>.007<br>(.00)</td><td>-.008<br>(.39)</td><td>Gsize</td><td>.003<br>(.00)</td><td>.004<br>(.00)</td><td>.003<br>(.00)</td><td>.003<br>(.00)</td><td>.001<br>(.00)</td></tr><tr><td>RIR</td><td>.006<br>(.00)</td><td>-.005<br>(.01)</td><td>.006<br>(.00)</td><td>.005<br>(.00)</td><td>.007<br>(.00)</td><td>INVEST</td><td>-.020<br>(.00)</td><td>-.021<br>(.00)</td><td>-.019<br>(.00)</td><td>-.023<br>(.00)</td><td>-.023<br>(.00)</td></tr><tr><td>PREG</td><td>-.007<br>(.12)</td><td>-.019<br>(.16)</td><td>-.003<br>(.57)</td><td>-.004<br>(.52)</td><td>-.016<br>(.00)</td><td>SCHOOL</td><td>-.006<br>(.00)</td><td>-.005<br>(.00)</td><td>-.007<br>(.00)</td><td>-.004<br>(.00)</td><td>-.003<br>(.00)</td></tr><tr><td>GDPC</td><td></td><td></td><td></td><td></td><td></td><td>CACCT</td><td>.012<br>(.00)</td><td>.013<br>(.00)</td><td>.012<br>(.00)</td><td>.006<br>(.00)</td><td>.002<br>(.35)</td></tr><tr><td>DINS</td><td>.014<br>(.00)</td><td>.024<br>(.00)</td><td>.007<br>(.23)</td><td>.014<br>(.03)</td><td>.020<br>(.00)</td><td>DCG</td><td>-.271<br>(.00)</td><td>-.253<br>(.00)</td><td>-.286<br>(.00)</td><td>.002<br>(.02)</td><td>-.003<br>(.38)</td></tr><tr><td>PR</td><td>.006<br>(.00)</td><td>.003<br>(.01)</td><td>.001<br>(.00)</td><td>.003<br>(.01)</td><td>.001<br>(.00)</td><td>cons</td><td>1.15<br>(.00)</td><td>1.18<br>(.00)</td><td>1.15<br>(.00)</td><td>1.20<br>(.00)</td><td>1.21<br>(.00)</td></tr><tr><td>TRADE</td><td>-.007<br>(.33)</td><td>-.004<br>(.57)</td><td>-.7e-6<br>(.94)</td><td>-.3e-6<br>(.97)</td><td>-.006<br>(.44)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>BMoney</td><td>-.002<br>(.00)</td><td>-.001<br>(.00)</td><td>-.002<br>(.02)</td><td>-.001<br>(.19)</td><td>-.004<br>(.00)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Debt</td><td>.002<br>(.00)</td><td>.006<br>(.09)</td><td>.001<br>(.11)</td><td>.002<br>(.00)</td><td>.002<br>(.00)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fiscal</td><td>-.003<br>(.00)</td><td>-.001<br>(.00)</td><td>-.004<br>(.00)</td><td>-.001<br>(.02)</td><td>-.004<br>(.00)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>cons</td><td>.255<br>(.00)</td><td>.151<br>(.00)</td><td>.248<br>(.00)</td><td>.126<br>(.00)</td><td>.384<br>(.00)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

nature of crisis dynamics, suggesting that factors beyond purely economic indicators may play a pivotal role in triggering financial crises. Moreover, the significant impact of financial crises on reducing the likelihood of economic crises is consistent with research conducted by Reinhart and Rogoff (2009). The findings of the present study contribute to this body of knowledge by employing a simultaneous equations approach, providing additional depth to the understanding of how financial and economic crises interact. Furthermore, a substantial proportion of the control variables, previously deemed significant based on the binary crisis measure, remain statistically significant. Additionally, some variables that were initially non-significant achieve significance. For instance, in the entire sample, the political regime sustains its insignificance, and the transaction volume, previously significant at the 10% threshold, experiences a loss of significance. Despite these nuanced variations, the overall magnitude of changes is not substantial. This also aligns with the broader literature on crisis determinants. For instance, the persistent importance of variables such as political regime aligns with the findings of Lensink et al. (1999) and Aisen and Veiga (2013), emphasizing the role of political stability in mitigating the probability of crises. Transaction volume, although losing significance at the 10% threshold, may still be indicative of broader economic activity, corroborating studies by scholars like Babecký et al. (2014), who highlighted the role of trade and transactions in crisis modeling.

In the context of the probability of an economic crisis, only the variable representing the political regime retains its lack of significance. This persistence in the non-significance of the political regime
<figure><img src="image_50.png" /><figcaption>Table 11. BMA results.</figcaption></figure>

<table><thead><tr><th colspan="10">Dependent variable: financial crisis</th><th colspan="10">Dependent variable: economic crisis</th></tr><tr><th></th><th colspan="2">Full</th><th colspan="2">Developed</th><th colspan="2">Emergent</th><th colspan="2">Bank</th><th colspan="2">Market</th><th></th><th colspan="2">Full</th><th colspan="2">developed</th><th colspan="2">Emergent</th><th colspan="2">Bank</th><th colspan="2">Market</th></tr></thead><tbody><tr><td>Variable</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>Variables</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td><td>PIP</td><td>TM</td></tr><tr><td>PrEcoC</td><td>.93</td><td>1.0</td><td>.07</td><td>1.0</td><td>.74</td><td>1.0</td><td>.06</td><td>1.0</td><td>.93</td><td>1.0</td><td>PrFinC</td><td>1.0</td><td>1.0</td><td>.99</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.64</td><td>.00</td></tr><tr><td>FL</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>FL</td><td>.22</td><td>.00</td><td>.04</td><td>.00</td><td>.10</td><td>.00</td><td>.04</td><td>.00</td><td>.67</td><td>1.0</td></tr><tr><td>GDPG</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>CPS</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>CACCT</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.44</td><td>.00</td><td>.99</td><td>1.0</td><td>1.0</td><td>1.0</td><td>M2RES</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>DCG</td><td>1.0</td><td>1.0</td><td>.18</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.51</td><td>.00</td><td>.99</td><td>1.0</td><td>INFL</td><td>1.0</td><td>1.0</td><td>.05</td><td>.00</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>TOTC</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>REER</td><td>1.0</td><td>1.0</td><td>.23</td><td>.00</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>KFLOW</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>PREG</td><td>.01</td><td>.00</td><td>.06</td><td>.00</td><td>.065</td><td>.00</td><td>.02</td><td>.00</td><td>.04</td><td>.00</td></tr><tr><td>M2RES</td><td>.19</td><td>.00</td><td>1.0</td><td>1.0</td><td>.65</td><td>1.0</td><td>.23</td><td>.00</td><td>.89</td><td>1.0</td><td>PR</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>INFL</td><td>.03</td><td>.00</td><td>1.0</td><td>1.0</td><td>.02</td><td>.00</td><td>.01</td><td>.00</td><td>.13</td><td>.00</td><td>TRADE</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>REER</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.05</td><td>.00</td><td>POPG</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>RIR</td><td>1.0</td><td>1.0</td><td>.27</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>Gsize</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>PREG</td><td>.02</td><td>.00</td><td>.09</td><td>.00</td><td>.04</td><td>.00</td><td>.06</td><td>.00</td><td>.93</td><td>1.0</td><td>INVEST</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>DINS<sup>12</sup></td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>SCHOOL</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>PR</td><td>.89</td><td>1.0</td><td>.18</td><td>.00</td><td>1.0</td><td>1.0</td><td>.68</td><td>1.0</td><td>.96</td><td>1.0</td><td>CACCT</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>TRADE</td><td>.94</td><td>1.0</td><td>.98</td><td>1.0</td><td>.96</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.13</td><td>.00</td><td>DCG</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td></tr><tr><td>BMoney</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.84</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.93</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Debt</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>.96</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fiscal</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PMP (Exact)</td><td>.66</td><td></td><td>.42</td><td></td><td>.27</td><td></td><td>.27</td><td></td><td>.56</td><td></td><td></td><td>.74</td><td></td><td>.66</td><td></td><td>.83</td><td></td><td>.92</td><td></td><td>.34</td><td></td><td></td></tr></tbody></table>

variable underscores its limited explanatory power in predicting economic crises. The minor alterations observed in significance levels and the sustained importance of key variables further underscore the robustness of the conclusions drawn from the simultaneous equations method, reinforcing the reliability of the study's analytical framework and the chosen indicators.

These findings corroborate and build upon the earlier conclusions, reinforcing the consistency and reliability of the results obtained through the application of the simultaneous equations method. The maintained significance of key variables, coupled with the limited impact of changes in significance levels, supports the credibility of the study's methodology and the relevance of the continuous indicators in capturing the complex dynamics of economic and financial crises.

In essence, the current findings contribute to and build upon the insights provided by previous works, offering a nuanced understanding of the intricate relationship between economic and financial crises. The alignment of results with established research adds credibility to the study's methodology and reinforces the relevance of continuous indicators in capturing the nuanced dynamics of crises.

The outcomes derived from the probabilistic method, as delineated in Table 11, introduce nuanced variations compared to the frequentist approach. The observed discrepancies between the results of the probabilistic and frequentist methods, particularly in terms of the significance of certain variables and the emergence of economic crisis probability as a determinant of financial crisis probability, resonate with similar challenges noted in previous works. The literature on financial and economic crises acknowledges the complexity of these phenomena, highlighting the need for diverse analytical tools to capture their multifaceted nature. Prior research, such as the works of Dabrowski et al. (2016) and Jemovic and Marinkovic (2021), has underscored the intricate relationship between economic and financial spheres. These studies, similar to the present one, emphasize the importance of employing diverse models to unravel the origins of crises and understand the dynamic interplay between real and financial factors. Notably, the economic crisis probability emerges as a noteworthy determinant of financial crisis probability across the entire dataset, as well as within emergent and market-based economies.

Contrastingly, certain variables, namely M2RES and INFL, which exhibited significance in the frequentist method, lose their significance in many instances under the probabilistic method. This shift in variable importance highlights the sensitivity of results to the chosen method and reinforces the need for a robust analytical framework that considers various statistical techniques. This discrepancy in findings underscores the importance of adopting diverse methodological approaches to comprehensively capture the complex dynamics inherent in financial and economic crises. The variable dynamics observed, where certain indicators lose or gain significance across different methodologies, align with methodological discussions in the broader literature. Scholars like Fernández et al. (2001) and Sala-I-Martin et al. (2004) have highlighted the challenges in identifying determinants of rare events, such as financial and
<figure><img src="image_51.png" /></figure>

economic crises. The adoption of model averaging approaches is consistent with the present study's choice to address uncertainty and optimize variable combinations based on their fit.

Moreover, the exclusion of the variable measuring the degree of capital account openness from the list of potential indicators for the probability of an economic crisis in the full sample underscores the methodological choices made in this study. This aligns with concerns raised in the literature about the static nature of these methods and their potential limitations in accounting for endogeneity. Indeed, the absence of dynamic considerations raises questions about the robustness of the findings, prompting the adoption of more sophisticated models in subsequent analyses. Previous works, such as those by Bussiere (2013) and Reinhart and Rogoff (2009), have emphasized the importance of distinguishing between various types of crises and considering their potential interactions, a perspective that resonates with the methodological evolution in this study.

These methodological considerations align with the broader discourse on model robustness and the necessity for approaches that address endogeneity concerns. The subsequent models employed in this study take into account the dynamic and endogenous nature of the relationships under investigation, aiming to enhance the reliability and validity of the results⁸. This strategic choice reflects a commitment to refining the analytical framework to better capture the intricate interplay between economic and financial crises in a more dynamic and comprehensive manner.

In essence, the methodological choices made in this study, informed by previous works and discussions in the literature, reflect a commitment to addressing the complexities of crisis dynamics. The nuanced approach taken, incorporating insights from diverse sources, contributes to the ongoing dialogue on refining methodologies for studying financial and economic crises, ultimately enhancing the robustness and reliability of the research.

Table 12 presents the outcomes of the P-VECM estimation for financial and economic crisis probabilities, shedding light on the intricate relationship between these crises and their determinants across various country types. The findings reveal several noteworthy patterns that resonate with previous works in the field.

The results indicate that the experience of a crisis in the preceding years significantly diminishes the likelihood of vulnerability in the present period, pointing towards a learning and prudence effect. This aligns with the findings of earlier studies such as those by Dabrowski et al. (2016) and Jemovic and Marinkovic (2021), emphasizing the importance of considering temporal dynamics in crisis analysis. The negative and significant error correction term associated with the relationship between past crises and the present likelihood of vulnerability supports the existence of a learning and prudence effect. This concept is consistent with the notion that countries may learn from past crises, adopting measures to mitigate future vulnerabilities.

In terms of financial crises, the deterioration of terms of trade emerges as a crucial factor, particularly impacting emerging economies and bank-based systems. This observation aligns with insights from works such as Bussiere (2013), which underscore the significance of external factors in shaping financial vulnerabilities. This highlights the importance of considering global economic conditions in assessing a country's susceptibility to financial crises. The differential impact on developed countries suggests a nuanced understanding of the role of exchange rate depreciation in these contexts.

For economic crises, the study identifies encouraging investment as a key protective factor across all country types. This echoes the emphasis on investment as a driver of economic stability in growth theories (Easterly & Rebelo, 1993) and aligns with the findings of studies emphasizing the multifaceted determinants of economic crises (Acemoglu, 2009).

The negative and significant error correction term associated with the relationship between economic and financial crises for all country types underscores the existence of a long-term connection between these crises. This echoes the findings of scholars like Reinhart and Rogoff (2009), who emphasize the interconnectedness of various crisis types and the importance of considering their dynamic relationships.

Moreover, the study reveals that experiencing an economic crisis has immediate destabilizing financial effects for all countries, while a financial crisis significantly increases the probability of an economic crisis, particularly for emergent countries. This observation aligns with the insights from the literature on the contagious nature of financial and economic crises (Babecký et al., 2014). This
<figure><img src="image_52.png" /><figcaption>Table 12. VECM results (financial crisis probability).</figcaption></figure>

<table><thead><tr><th rowspan="3"></th><th rowspan="3"></th><th colspan="12">Full sample</th></tr><tr><th colspan="4">With subprime</th><th colspan="4">Without subprime</th></tr><tr><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th></tr></thead><tbody><tr><td rowspan="20">Financial crisis</td><td>ECT</td><td></td><td>.116</td><td>.00</td><td></td><td></td><td>.099</td><td>.00</td><td></td><td></td></tr><tr><td>PrFinC (-1)</td><td></td><td>-.230</td><td>.00</td><td>41.0</td><td></td><td>-.304</td><td>.00</td><td>55.2</td><td></td></tr><tr><td>PrFinC(-2)</td><td></td><td>-.226</td><td>.00</td><td>(.00)</td><td></td><td>-.253</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>PrEcoC(-1)</td><td>-.477</td><td>-.241</td><td>.00</td><td>29.9</td><td>-.485</td><td>-.188</td><td>.00</td><td>15.1</td><td></td></tr><tr><td>PrEcoC(-2)</td><td>(.00)</td><td>.060</td><td>.20</td><td>(.00)</td><td>(.00)</td><td>-.014</td><td>.76</td><td>(.00)</td><td></td></tr><tr><td>FL(-1)</td><td>-.614</td><td>-.013</td><td>.01</td><td>5.88</td><td>-.648</td><td>-.016</td><td>.00</td><td>8.67</td><td></td></tr><tr><td>FL(-2)</td><td>(.00)</td><td>-.001</td><td>.83</td><td>(.05)</td><td>(.00)</td><td>-.003</td><td>.50</td><td>(.01)</td><td></td></tr><tr><td>GDPG(-1)</td><td>-.516</td><td>.001</td><td>.05</td><td>4.39</td><td>-.527</td><td>.008</td><td>.36</td><td>2.41</td><td></td></tr><tr><td>GDPG(-2)</td><td>(.00)</td><td>5E-5</td><td>.94</td><td>(.11)</td><td>(.00)</td><td>-.005</td><td>.48</td><td>(.29)</td><td></td></tr><tr><td>CACCT(-1)</td><td>-.526</td><td>.004</td><td>.00</td><td>12.5</td><td>-.545</td><td>.003</td><td>.02</td><td>5.88</td><td></td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>-.001</td><td>.17</td><td>(.00)</td><td>(.00)</td><td>-.001</td><td>.49</td><td>(.05)</td><td></td></tr><tr><td>DCG(-1)</td><td>-.008</td><td>-.022</td><td>.17</td><td>11.4</td><td>-.006</td><td>-.016</td><td>.34</td><td>5.25</td><td></td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>.039</td><td>.01</td><td>(.00)</td><td>(.00)</td><td>.028</td><td>.09</td><td>(.07)</td><td></td></tr><tr><td>TOTC(-1)</td><td>-.043</td><td>.370</td><td>.00</td><td>115.</td><td>-.021</td><td>.371</td><td>.00</td><td>103</td><td></td></tr><tr><td>TOTC(-2)</td><td>(.00)</td><td>.227</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>.223</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>KFLOW(-1)</td><td>-.542</td><td>-.001</td><td>.49</td><td>.478</td><td>-.576</td><td>-.005</td><td>.04</td><td>4.03</td><td></td></tr><tr><td>KFLOW(-2)</td><td>(.00)</td><td>-6E-5</td><td>.78</td><td>(.78)</td><td>(.00)</td><td>-7E-5</td><td>.80</td><td>(.13)</td><td></td></tr><tr><td>REER(-1)</td><td>-.507</td><td>.001</td><td>.00</td><td>66.4</td><td>-.546</td><td>.007</td><td>.00</td><td>13.2</td><td></td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.006</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.002</td><td>.20</td><td>(.00)</td><td></td></tr><tr><td>RIR(-1)</td><td>.027</td><td>-2E-5</td><td>.59</td><td>1.58</td><td>.011</td><td>5E-6</td><td>.19</td><td>3.08</td><td></td></tr><tr><td>RIR(-2))</td><td>(.00)</td><td>3E-5</td><td>.45</td><td>(.45)</td><td>(.00)</td><td>7E-6</td><td>.09</td><td>(.21)</td><td></td></tr><tr><td>PR(-1))</td><td>-.545</td><td>-.008</td><td>.05</td><td>3.64</td><td>-.574</td><td>-.003</td><td>.38</td><td>.749</td><td></td></tr><tr><td>PR(-2))</td><td>(.00)</td><td>.001</td><td>.71</td><td>(.16)</td><td>(.00)</td><td>5E-5</td><td>.88</td><td>(.68)</td><td></td></tr><tr><td>TRADE(-1)</td><td>-.565</td><td>-.006</td><td>.01</td><td>5.59</td><td>-.593</td><td>-.004</td><td>.01</td><td>9.00</td><td></td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-8E-4</td><td>.77</td><td>(.06)</td><td>(.00)</td><td>-.003</td><td>.10</td><td>(.01)</td><td></td></tr><tr><td>MONEY(-1)</td><td>-.560</td><td>.001</td><td>.00</td><td>31.1</td><td>-.592</td><td>.001</td><td>.00</td><td>27.6</td><td></td></tr><tr><td>MONEY(-2)</td><td>(.00)</td><td>.007</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>.004</td><td>.08</td><td>(.00)</td><td></td></tr><tr><td>DEBT(-1)</td><td>-.528</td><td>-.003</td><td>.21</td><td>1.58</td><td>-.554</td><td>-.004</td><td>.089</td><td>3.87</td><td></td></tr><tr><td>DEBT(-2)</td><td>(.00)</td><td>.001</td><td>.61</td><td>(.45)</td><td>(.00)</td><td>.002</td><td>.17</td><td>(.14)</td><td></td></tr><tr><td>FISCAL(-1)</td><td>-.558</td><td>.001</td><td>.39</td><td>14.6</td><td>-.577</td><td>-.005</td><td>.68</td><td>8.30</td><td></td></tr><tr><td>FISCAL(-2)</td><td>(.00)</td><td>-.004</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.003</td><td>.00</td><td>(.01)</td><td></td></tr><tr><td>C</td><td></td><td>-.001</td><td>.46</td><td></td><td></td><td>-.006</td><td>.77</td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>59.8</td><td></td><td></td><td></td><td>62.3</td><td></td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.410</td><td></td><td></td><td></td><td>.404</td><td></td><td></td><td></td></tr><tr><td rowspan="20">Economic crisis</td><td>ECT</td><td></td><td>-.006</td><td>.00</td><td></td><td></td><td>.067</td><td>.00</td><td></td><td></td></tr><tr><td>PrEcoC (-1)</td><td></td><td>-.633</td><td>.00</td><td>48.4</td><td></td><td>-.576</td><td>.00</td><td>31.5</td><td></td></tr><tr><td>PrEcoC(-2)</td><td></td><td>-.372</td><td>.00</td><td>(.00)</td><td></td><td>-.380</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>PrFinC(-1)</td><td>.002</td><td>.195</td><td>.00</td><td>37.3</td><td>-.001</td><td>.220</td><td>.00</td><td>46.5</td><td></td></tr><tr><td>PrFinC(-2)</td><td>(.00)</td><td>.032</td><td>.26</td><td>(.00)</td><td>(.00)</td><td>.070</td><td>.02</td><td>(.00)</td><td></td></tr><tr><td>CPS(-1)</td><td>-.138</td><td>5E-5</td><td>.90</td><td>.488</td><td>-.164</td><td>.003</td><td>.29</td><td>3.26</td><td></td></tr><tr><td>CPS(-2)</td><td>(.00)</td><td>.003</td><td>.50</td><td>(.78)</td><td>(.00)</td><td>.005</td><td>.16</td><td>(.19)</td><td></td></tr><tr><td>M2RES(-1)</td><td>-.176</td><td>-.002</td><td>.71</td><td>5.33</td><td>-.189</td><td>-.007</td><td>.25</td><td>2.12</td><td></td></tr><tr><td>M2RES(-2)</td><td>(.00)</td><td>-.001</td><td>.02</td><td>(.06)</td><td>(.00)</td><td>-.004</td><td>.47</td><td>(.34)</td><td></td></tr><tr><td>INFL(-1)</td><td>.003</td><td>5E-5</td><td>.00</td><td>26.7</td><td>.004</td><td>4E-5</td><td>.00</td><td>14.6</td><td></td></tr><tr><td>INFL(-2)</td><td>(.39)</td><td>3E-5</td><td>.00</td><td>(.00)</td><td>(.48)</td><td>2E-5</td><td>.01</td><td>(.00)</td><td></td></tr><tr><td>REER(-1)</td><td>-.175</td><td>.001</td><td>.50</td><td>6.09</td><td>-.160</td><td>-.002</td><td>.43</td><td>1.19</td><td></td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.006</td><td>.01</td><td>(.04)</td><td>(.00)</td><td>-.001</td><td>.53</td><td>(.55)</td><td></td></tr><tr><td>PR(-1)</td><td>-.095</td><td>-.002</td><td>.00</td><td>23.7</td><td>-.148</td><td>-.002</td><td>.00</td><td>23.8</td><td></td></tr><tr><td>PR(-2))</td><td>(.00)</td><td>-.001</td><td>.03</td><td>(.00)</td><td>(.00)</td><td>-.001</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>TRADE(-1)</td><td>-.176</td><td>.004</td><td>.16</td><td>2.30</td><td>-.193</td><td>.004</td><td>.06</td><td>5.15</td><td></td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.001</td><td>.57</td><td>(.31)</td><td>(.00)</td><td>.002</td><td>.25</td><td>(.07)</td><td></td></tr><tr><td>POPG(-1)</td><td>-.181</td><td>-.029</td><td>.00</td><td>13.8</td><td>-.196</td><td>-.016</td><td>.04</td><td>4.16</td><td></td></tr><tr><td>POPG(-2)</td><td>(.00)</td><td>-.010</td><td>.17</td><td>(.00)</td><td>(.00)</td><td>-.007</td><td>.36</td><td>(.12)</td><td></td></tr><tr><td>GSIZE(-1)</td><td>-.187</td><td>.005</td><td>.04</td><td>4.04</td><td>-.205</td><td>.001</td><td>.48</td><td>.778</td><td></td></tr><tr><td>GSIZE(-2)</td><td>(.00)</td><td>.009</td><td>.72</td><td>(.13)</td><td>(.00)</td><td>.001</td><td>.57</td><td>(.67)</td><td></td></tr><tr><td>INVEST(-1)</td><td>-.264</td><td>-.017</td><td>.00</td><td>65.3</td><td>-.313</td><td>-.015</td><td>.00</td><td>44.8</td><td></td></tr><tr><td>INVEST(-2)</td><td>(.00)</td><td>-.011</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.011</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>SCHOOL(-1)</td><td>-.182</td><td>-7E-5</td><td>.88</td><td>.619</td><td>-.197</td><td>-.006</td><td>.16</td><td>2.82</td><td></td></tr><tr><td>SCHOOL(-2)</td><td>(.00)</td><td>-.004</td><td>.44</td><td>(.73)</td><td>(.00)</td><td>-.004</td><td>.39</td><td>(.24)</td><td></td></tr><tr><td>CACCT(-1)</td><td>-.167</td><td>.001</td><td>.41</td><td>1.22</td><td>-.166</td><td>.002</td><td>.87</td><td>.258</td><td></td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>-.008</td><td>.59</td><td>(.54)</td><td>(.00)</td><td>-.007</td><td>.66</td><td>(.87)</td><td></td></tr><tr><td>DCG(-1)</td><td>.013</td><td>-.209</td><td>.00</td><td>35.3</td><td>.013</td><td>-.172</td><td>.00</td><td>21.3</td><td></td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>-.106</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.101</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>C</td><td></td><td>.001</td><td>.494</td><td></td><td></td><td>.005</td><td>.82</td><td></td><td></td></tr><tr><td>AIC</td><td></td><td>54.1</td><td></td><td></td><td></td><td>57.2</td><td></td><td></td><td></td></tr><tr><td>R-squared</td><td></td><td>.293</td><td></td><td></td><td></td><td>.266</td><td></td><td></td><td></td></tr></tbody></table>

(Continued)
<table><caption>Table 12. Continued.</caption><thead><tr><th rowspan="3"></th><th rowspan="3"></th><th colspan="10">Developed</th></tr><tr><th colspan="4">With subprime</th><th colspan="4">Without subprime</th></tr><tr><th>LTIE</th><th>Coef</th><th>Prob</th><th>Wald</th><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th></tr></thead><tbody><tr><td rowspan="24">Financial crisis</td><td>ECT</td><td></td><td>.025</td><td>.000</td><td></td><td></td><td>.033</td><td>.00</td><td></td></tr><tr><td>PrFinC(-1)</td><td></td><td>-.105</td><td>.034</td><td>20.1</td><td></td><td>-.241</td><td>.00</td><td>21.8</td></tr><tr><td>PrFinC(-2)</td><td></td><td>-.213</td><td>.000</td><td>(.00)</td><td></td><td>-.022</td><td>.66</td><td>(.00)</td></tr><tr><td>PrEcoC (-1)</td><td>-.324</td><td>-.060</td><td>.000</td><td>15.1</td><td>-.318</td><td>-.042</td><td>.01</td><td>6.57</td></tr><tr><td>PrEcoC (-2)</td><td>(.00)</td><td>.003</td><td>.833</td><td>(.00)</td><td>(.00)</td><td>-.009</td><td>.54</td><td>(.03)</td></tr><tr><td>FL(-1)</td><td>-.330</td><td>-.005</td><td>.240</td><td>5.79</td><td>-.422</td><td>-.002</td><td>.28</td><td>1.52</td></tr><tr><td>FL(-2)</td><td>(.00)</td><td>-.007</td><td>.066</td><td>(.05)</td><td>(.00)</td><td>-.001</td><td>.58</td><td>(.46)</td></tr><tr><td>GDPG(-1)</td><td>-.203</td><td>.002</td><td>.000</td><td>15.0</td><td>-.232</td><td>.002</td><td>.00</td><td>18.8</td></tr><tr><td>GDPG(-2)</td><td>(.00)</td><td>.002</td><td>.696</td><td>(.00)</td><td>(.00)</td><td>.001</td><td>.05</td><td>(.00)</td></tr><tr><td>CACCT(-1)</td><td>-.326</td><td>.001</td><td>.861</td><td>6.59</td><td>-.409</td><td>-.001</td><td>.03</td><td>16.3</td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>-.002</td><td>.012</td><td>(.03)</td><td>(.00)</td><td>-.002</td><td>.00</td><td>(.00)</td></tr><tr><td>TOTC(-1)</td><td>.037</td><td>.155</td><td>.000</td><td>21.4</td><td>.045</td><td>.088</td><td>.00</td><td>10.2</td></tr><tr><td>TOTC(-2)</td><td>(.00)</td><td>.081</td><td>.000</td><td>(.00)</td><td>(.00)</td><td>.008</td><td>.70</td><td>(.00)</td></tr><tr><td>KFLOW(-1)</td><td>-.331</td><td>-.001</td><td>.344</td><td>1.48</td><td>-.380</td><td>-.002</td><td>.07</td><td>19.1</td></tr><tr><td>KFLOW(-2)</td><td>(.00)</td><td>4E-5</td><td>.690</td><td>(.47)</td><td>(.00)</td><td>.003</td><td>.00</td><td>(.00)</td></tr><tr><td>M2RES(-1)</td><td>-.419</td><td>.003</td><td>.098</td><td>2.82</td><td>-.463</td><td>.002</td><td>.04</td><td>15.3</td></tr><tr><td>M2RES(-2)</td><td>(.00)</td><td>-.001</td><td>.432</td><td>(.24)</td><td>(.00)</td><td>.004</td><td>.00</td><td>(.00)</td></tr><tr><td>INFL(-1)</td><td>-.011</td><td>.001</td><td>.561</td><td>1.15</td><td>-.078</td><td>-.001</td><td>.05</td><td>5.39</td></tr><tr><td>INFL(-2)</td><td>(.15)</td><td>9E-5</td><td>.461</td><td>(.56)</td><td>(.00)</td><td>.001</td><td>.14</td><td>(.06)</td></tr><tr><td>REER(-1)</td><td>-.335</td><td>.003</td><td>.081</td><td>3.12</td><td>-.404</td><td>.001</td><td>.52</td><td>1.06</td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.001</td><td>.531</td><td>(.20)</td><td>(.00)</td><td>-.001</td><td>.37</td><td>(.58)</td></tr><tr><td>TRADE(-1)</td><td>-.329</td><td>-.001</td><td>.577</td><td>1.58</td><td>-.399</td><td>.001</td><td>.13</td><td>2.35</td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.002</td><td>.272</td><td>(.45)</td><td>(.00)</td><td>-5E-5</td><td>.65</td><td>(.30)</td></tr><tr><td>MONEY(-1)</td><td>-.328</td><td>-.002</td><td>.103</td><td>17.2</td><td>-.401</td><td>-2E-5</td><td>.65</td><td>.77</td></tr><tr><td>MONEY(-2)</td><td>(.00)</td><td>.005</td><td>.000</td><td>(.00)</td><td>(.00)</td><td>4E-5</td><td>.43</td><td>(.67)</td></tr><tr><td>DEBT(-1)</td><td>-.305</td><td>-.002</td><td>.127</td><td>5.06</td><td>-.364</td><td>5E-5</td><td>.52</td><td>.784</td></tr><tr><td>DEBT(-2)</td><td>(.00)</td><td>-.001</td><td>.186</td><td>(.07)</td><td>(.00)</td><td>-4E-5</td><td>.56</td><td>(.67)</td></tr><tr><td>FISCAL(-1)</td><td>-.315</td><td>2E-5</td><td>.981</td><td>13.6</td><td>-.354</td><td>-.002</td><td>.00</td><td>19.9</td></tr><tr><td>FISCAL(-2)</td><td>(.00)</td><td>-.003</td><td>.003</td><td>(.00)</td><td>(.00)</td><td>-.002</td><td>.00</td><td>(.00)</td></tr><tr><td>C</td><td></td><td>.008</td><td>.436</td><td></td><td></td><td>.001</td><td>.87</td><td></td></tr><tr><td>AIC</td><td></td><td>39.7</td><td></td><td></td><td></td><td>53.0</td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.350</td><td></td><td></td><td></td><td>.390</td><td></td><td></td></tr><tr><td>Economic crisis</td><td>ECT</td><td></td><td>-.845</td><td>.000</td><td></td><td></td><td>.743</td><td></td><td></td></tr><tr><td></td><td>PrEcoC (-1)</td><td></td><td>-.247</td><td>.081</td><td>3.14</td><td></td><td>-.664</td><td>.00</td><td>12.4</td></tr><tr><td></td><td>PrEcoC (-2)</td><td></td><td>-.075</td><td>.549</td><td>(.20)</td><td></td><td>-.179</td><td>.00</td><td>(.00)</td></tr><tr><td></td><td>PrFinC (-1)</td><td>.054</td><td>.094</td><td>.357</td><td>1.35</td><td>.022</td><td>-.033</td><td>.33</td><td>.070</td></tr><tr><td></td><td>PrFinC (-2)</td><td>(.00)</td><td>-.053</td><td>.566</td><td>(.50)</td><td>(.00)</td><td>-.003</td><td>.79</td><td>(.96)</td></tr><tr><td></td><td>CPS(-1)</td><td>-.107</td><td>-.008</td><td>.158</td><td>1.99</td><td>-.176</td><td>.006</td><td>.97</td><td>15.8</td></tr><tr><td></td><td>CPS(-2)</td><td>(.00)</td><td>.007</td><td>.870</td><td>(.36)</td><td>(.00)</td><td>.007</td><td>.01</td><td>(.00)</td></tr><tr><td></td><td>M2RES(-1)</td><td>-.178</td><td>-.003</td><td>.558</td><td>.881</td><td>-.213</td><td>-.001</td><td>.00</td><td>15.0</td></tr><tr><td></td><td>M2RES(-2)</td><td>(.00)</td><td>-.003</td><td>.527</td><td>(.64)</td><td>(.00)</td><td>-.001</td><td>.00</td><td>(.00)</td></tr><tr><td></td><td>PR(-1)</td><td>-.028</td><td>-.001</td><td>.112</td><td>3.58</td><td>-.181</td><td>-.002</td><td>.01</td><td>11.7</td></tr><tr><td></td><td>PR(-2)</td><td>(.00)</td><td>-.007</td><td>.280</td><td>(.16)</td><td>(.00)</td><td>-.009</td><td>.00</td><td>(.00)</td></tr><tr><td></td><td>TRADE(-1)</td><td>-.157</td><td>.001</td><td>.041</td><td>14.65</td><td>-.213</td><td>.004</td><td>.13</td><td>6.60</td></tr><tr><td></td><td>TRADE(-2)</td><td>(.00)</td><td>.001</td><td>.002</td><td>(.00)</td><td>(.00)</td><td>.007</td><td>.17</td><td>(.03)</td></tr><tr><td></td><td>POPG(-1)</td><td>-.170</td><td>-.021</td><td>.042</td><td>4.22</td><td>-.226</td><td>-.027</td><td>.03</td><td>6.36</td></tr><tr><td></td><td>POPG(-2)</td><td>(.00)</td><td>.001</td><td>.923</td><td>(.12)</td><td>(.00)</td><td>.004</td><td>.01</td><td>(.04)</td></tr><tr><td></td><td>GSIZE(-1)</td><td>-.140</td><td>.014</td><td>.002</td><td>9.48</td><td>-.212</td><td>.004</td><td>.68</td><td>3.51</td></tr><tr><td></td><td>GSIZE(-2)</td><td>(.00)</td><td>.002</td><td>.589</td><td>(.00)</td><td>(.00)</td><td>-.002</td><td>.10</td><td>(.17)</td></tr><tr><td></td><td>INVEST(-1)</td><td>-.078</td><td>-.009</td><td>.009</td><td>7.88</td><td>-.102</td><td>-.016</td><td>.35</td><td>12.7</td></tr><tr><td></td><td>INVEST(-2)</td><td>(.00)</td><td>-.006</td><td>.092</td><td>(.01)</td><td>(.00)</td><td>-.007</td><td>.00</td><td>(.00)</td></tr><tr><td></td><td>SCHOOL(-1)</td><td>-.161</td><td>.004</td><td>.475</td><td>.540</td><td>-.207</td><td>-.009</td><td>.08</td><td>4.63</td></tr><tr><td></td><td>SCHOOL(-2)</td><td>(.00)</td><td>4E-5</td><td>.935</td><td>(.76)</td><td>(.00)</td><td>-.002</td><td>.04</td><td>(.09)</td></tr><tr><td></td><td>CACCT(-1)</td><td>-.176</td><td>.004</td><td>.872</td><td>5.75</td><td>-.232</td><td>.003</td><td>.52</td><td>2.54</td></tr><tr><td></td><td>CACCT(-2)</td><td>(.00)</td><td>-.005</td><td>.026</td><td>(.05)</td><td>(.00)</td><td>-.002</td><td>.30</td><td>(.28)</td></tr><tr><td></td><td>DCG(-1)</td><td>.007</td><td>-.082</td><td>.023</td><td>5.14</td><td>.012</td><td>-.169</td><td>.44</td><td>7.55</td></tr><tr><td></td><td>(.00)</td><td></td><td></td><td>(.07)</td><td>(.00)</td><td></td><td></td><td></td><td>(.02)</td></tr><tr><td></td><td>DCG(-2)</td><td></td><td>-.037</td><td>.277</td><td></td><td></td><td>-.060</td><td>.00</td><td></td></tr><tr><td></td><td>C</td><td></td><td>.006</td><td>.824</td><td></td><td></td><td>.002</td><td>.24</td><td></td></tr><tr><td></td><td>AIC</td><td></td><td>27.1</td><td></td><td></td><td></td><td>36.1</td><td>.92</td><td></td></tr><tr><td></td><td>R-Squared</td><td></td><td>.396</td><td></td><td></td><td></td><td>.270</td><td></td><td></td></tr></tbody></table>

(Continued)
<figure><img src="image_53.png" /><figcaption>Table 12. Continued.</figcaption></figure>

<table><thead><tr><th rowspan="3"></th><th rowspan="3"></th><th colspan="10">Emergent</th></tr><tr><th colspan="4">With subprime</th><th colspan="4">Without subprime</th></tr><tr><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th><th>LTIE</th><th>coef</th><th>Prob</th><th>Wald</th></tr></thead><tbody><tr><td rowspan="21">Financial crisis</td><td>ECT</td><td></td><td>.107</td><td>.00</td><td></td><td></td><td>.024</td><td>.00</td><td></td></tr><tr><td>PrFinC(-1)</td><td></td><td>-.298</td><td>.00</td><td>27.6</td><td></td><td>-.290</td><td>.00</td><td>27.0</td></tr><tr><td>PrFinC(-2)</td><td></td><td>-.207</td><td>.00</td><td>(.00)</td><td></td><td>-.217</td><td>.00</td><td>(.00)</td></tr><tr><td>PrEcoC(-1)</td><td>-.507</td><td>-.163</td><td>.00</td><td>9.84</td><td>-.506</td><td>-.049</td><td>.29</td><td>1.47</td></tr><tr><td>PrEcoC(-2)</td><td>(.00)</td><td>.027</td><td>.60</td><td>(.00)</td><td>(.00)</td><td>.023</td><td>.60</td><td>(.47)</td></tr><tr><td>FL(-1)</td><td>-.660</td><td>-.015</td><td>.04</td><td>4.19</td><td>-.671</td><td>-.001</td><td>.87</td><td>.133</td></tr><tr><td>FL(-2)</td><td>(.00)</td><td>-.003</td><td>.96</td><td>(.12)</td><td>(.00)</td><td>.002</td><td>.74</td><td>(.93)</td></tr><tr><td>GDPG(-1)</td><td>-.627</td><td>.003</td><td>.75</td><td>.198</td><td>-.633</td><td>-.009</td><td>.045</td><td>.622</td></tr><tr><td>GDPG(-2)</td><td>(.00)</td><td>.004</td><td>.67</td><td>(.90)</td><td>(.00)</td><td>-.006</td><td>.57</td><td>(.73)</td></tr><tr><td>DCG(-1)</td><td>-.010</td><td>-.012</td><td>.64</td><td>1.62</td><td>.002</td><td>.026</td><td>.28</td><td>7.87</td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>.023</td><td>.33</td><td>(.44)</td><td>(.00)</td><td>.065</td><td>.00</td><td>(.01)</td></tr><tr><td>TOTC(-1)</td><td>-.064</td><td>.410</td><td>.00</td><td>68.5</td><td>-.090</td><td>.402</td><td>.00</td><td>74.3</td></tr><tr><td>TOTC(-2)</td><td>(.00)</td><td>.231</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>.236</td><td>.00</td><td>(.00)</td></tr><tr><td>KFLOW(-1)</td><td>-.606</td><td>-.001</td><td>.72</td><td>.298</td><td>-.617</td><td>-.001</td><td>.02</td><td>6.42</td></tr><tr><td>KFLOW(-2)</td><td>(.00)</td><td>-.002</td><td>.65</td><td>(.86)</td><td>(.00)</td><td>-.001</td><td>.04</td><td>(.04)</td></tr><tr><td>M2RES(-1)</td><td>-.490</td><td>.010</td><td>.00</td><td>57.1</td><td>-.554</td><td>.008</td><td>.00</td><td>51.8</td></tr><tr><td>M2RES(-2)</td><td>(.00)</td><td>.003</td><td>.02</td><td>(.00)</td><td>(.00)</td><td>.002</td><td>.04</td><td>(.00)</td></tr><tr><td>REER(-1)</td><td>-.547</td><td>.001</td><td>.00</td><td>34.7</td><td>-.577</td><td>.007</td><td>.00</td><td>11.9</td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.007</td><td>.02</td><td>(.00)</td><td>(.00)</td><td>-.002</td><td>.21</td><td>(.00)</td></tr><tr><td>RIR(-1)</td><td>.002</td><td>-1E-6</td><td>.84</td><td>.247</td><td>.007</td><td>3E-6</td><td>.53</td><td>.487</td></tr><tr><td>RIR(-2)</td><td>(.00)</td><td>1E-6</td><td>.75</td><td>(.88)</td><td>(.00)</td><td>3E-6</td><td>.57</td><td>(.78)</td></tr><tr><td>PR(-1)</td><td>-.591</td><td>-.008</td><td>.24</td><td>1.55</td><td>-.605</td><td>.006</td><td>.23</td><td>1.96</td></tr><tr><td>PR(-2)</td><td>(.00)</td><td>.004</td><td>.54</td><td>(.45)</td><td>(.00)</td><td>.003</td><td>.48</td><td>(.37)</td></tr><tr><td>TRADE(-1)</td><td>-.630</td><td>-.005</td><td>.13</td><td>2.38</td><td>-.647</td><td>.001</td><td>.44</td><td>.595</td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.001</td><td>.61</td><td>(.30)</td><td>(.00)</td><td>2E-5</td><td>.93</td><td>(.74)</td></tr><tr><td>MONEY(-1)</td><td>-.618</td><td>.001</td><td>.01</td><td>11.1</td><td>-.635</td><td>8E-5</td><td>.71</td><td>.340</td></tr><tr><td>MONEY(-2)</td><td>(.00)</td><td>.001</td><td>.05</td><td>(.00)</td><td>(.00)</td><td>.001</td><td>.64</td><td>(.84)</td></tr><tr><td>DEBT(-1)</td><td>-.577</td><td>-.003</td><td>.42</td><td>.693</td><td>-.597</td><td>-.002</td><td>.32</td><td>2.00</td></tr><tr><td>DEBT(-2)</td><td>(.00)</td><td>.001</td><td>.74</td><td>(.70)</td><td>(.00)</td><td>.003</td><td>.25</td><td>(.36)</td></tr><tr><td>FISCAL(-1)</td><td>-.606</td><td>.006</td><td>.72</td><td>6.77</td><td>-.620</td><td>.005</td><td>.67</td><td>1.04</td></tr><tr><td>FISCAL(-2)</td><td>(.00)</td><td>-.004</td><td>.00</td><td>(.03)</td><td>(.00)</td><td>-.001</td><td>.33</td><td>(.59)</td></tr><tr><td>C</td><td></td><td>-9E-5</td><td>.97</td><td></td><td></td><td>.008</td><td>.79</td><td></td></tr><tr><td>AIC</td><td></td><td>64.3</td><td></td><td></td><td></td><td>71.9</td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.470</td><td></td><td></td><td></td><td>.431</td><td></td><td></td></tr><tr><td rowspan="21">Economic crisis</td><td>ECT</td><td></td><td>.234</td><td>.00</td><td></td><td></td><td>.056</td><td>.00</td><td></td></tr><tr><td>PrEcoC(-1)</td><td></td><td>-.764</td><td>.00</td><td>33.5</td><td></td><td>-.661</td><td>.00</td><td>25.3</td></tr><tr><td>PrEcoC(-2)</td><td></td><td>-.491</td><td>.00</td><td>(.00)</td><td></td><td>-.475</td><td>.00</td><td>(.00)</td></tr><tr><td>PrFinC(-1)</td><td>-.007</td><td>.171</td><td>.00</td><td>17.4</td><td>-.023</td><td>.224</td><td>.00</td><td>33.8</td></tr><tr><td>PrFinC(-2)</td><td>(.00)</td><td>.038</td><td>.28</td><td>(.00)</td><td>(.00)</td><td>.080</td><td>.02</td><td>(.00)</td></tr><tr><td>CPS(-1)</td><td>-.145</td><td>.003</td><td>.61</td><td>2.26</td><td>-.208</td><td>.008</td><td>.02</td><td>7.83</td></tr><tr><td>CPS(-2)</td><td>(.00)</td><td>.009</td><td>.17</td><td>(.32)</td><td>(.00)</td><td>.006</td><td>.08</td><td>(.01)</td></tr><tr><td>M2RES(-1)</td><td>-.011</td><td>.003</td><td>.00</td><td>7.66</td><td>-.142</td><td>.002</td><td>.05</td><td>4.73</td></tr><tr><td>M2RES(-2)</td><td>(.00)</td><td>.008</td><td>.54</td><td>(.02)</td><td>(.00)</td><td>.001</td><td>.16</td><td>(.09)</td></tr><tr><td>INFL(-1)</td><td>.002</td><td>6E-5</td><td>.00</td><td>18.6</td><td>-.007</td><td>5E-5</td><td>.00</td><td>12.4</td></tr><tr><td>INFL(-2)</td><td>(.91)</td><td>3E-5</td><td>.00</td><td>(.00)</td><td>(.81)</td><td>3E-5</td><td>.02</td><td>(.00)</td></tr><tr><td>REER(-1)</td><td>-.191</td><td>.001</td><td>.63</td><td>3.37</td><td>-.219</td><td>-7E-5</td><td>.76</td><td>.243</td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.006</td><td>.06</td><td>(.18)</td><td>(.00)</td><td>-9E-5</td><td>.72</td><td>(.88)</td></tr><tr><td>PR(-1)</td><td>-.057</td><td>-.002</td><td>.00</td><td>15.4</td><td>-.224</td><td>-.002</td><td>.00</td><td>14.0</td></tr><tr><td>PR(-2)</td><td>(.00)</td><td>-.001</td><td>.20</td><td>(.00)</td><td>(.00)</td><td>-.001</td><td>.11</td><td>(.00)</td></tr><tr><td>TRADE(-1)</td><td>-.192</td><td>.003</td><td>.43</td><td>2.89</td><td>-.222</td><td>.003</td><td>.17</td><td>2.45</td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.006</td><td>.14</td><td>(.23)</td><td>(.00)</td><td>.001</td><td>.49</td><td>(.29)</td></tr><tr><td>POPG(-1)</td><td>-.194</td><td>-.025</td><td>.03</td><td>4.67</td><td>-.222</td><td>-.021</td><td>.07</td><td>4.03</td></tr><tr><td>POPG(-2)</td><td>(.00)</td><td>-.010</td><td>.39</td><td>(.09)</td><td>(.00)</td><td>-.015</td><td>.19</td><td>(.13)</td></tr><tr><td>GSIZE(-1)</td><td>-.197</td><td>.003</td><td>.30</td><td>1.04</td><td>-.224</td><td>-.002</td><td>.91</td><td>.683</td></tr><tr><td>GSIZE(-2)</td><td>(.00)</td><td>.002</td><td>.94</td><td>(.59)</td><td>(.00)</td><td>.002</td><td>.41</td><td>(.71)</td></tr><tr><td>INVEST(-1)</td><td>-.413</td><td>-.019</td><td>.00</td><td>40.8</td><td>-.482</td><td>-.015</td><td>.00</td><td>29.7</td></tr><tr><td>INVEST(-2)</td><td>(.00)</td><td>-.012</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.011</td><td>.00</td><td>(.00)</td></tr><tr><td>SCHOOL(-1)</td><td>-.201</td><td>-.008</td><td>.40</td><td>1.33</td><td>-.223</td><td>-.003</td><td>.56</td><td>1.80</td></tr><tr><td>SCHOOL(-2)</td><td>(.00)</td><td>-.007</td><td>.43</td><td>(.51)</td><td>(.00)</td><td>-.006</td><td>.22</td><td>(.40)</td></tr><tr><td>CACCT(-1)</td><td>-.172</td><td>.002</td><td>.36</td><td>1.12</td><td>-.173</td><td>.001</td><td>.51</td><td>.536</td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>.001</td><td>.46</td><td>(.57)</td><td>(.00)</td><td>.001</td><td>.64</td><td>(.76)</td></tr><tr><td>DCG(-1)</td><td>.017</td><td>-.242</td><td>.00</td><td>18.5</td><td>.022</td><td>-.189</td><td>.00</td><td>13.4</td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>-.134</td><td>.00</td><td>(.00)</td><td>(.00)</td><td>-.119</td><td>.01</td><td>(.00)</td></tr><tr><td>C</td><td></td><td>.003</td><td>.40</td><td></td><td></td><td>.001</td><td>.96</td><td></td></tr><tr><td>AIC</td><td></td><td>56.2</td><td></td><td></td><td></td><td>64.5</td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.291</td><td></td><td></td><td></td><td>.246</td><td></td><td></td></tr></tbody></table>

(Continued)