<figure><img src="image_54.png" /><figcaption>Table 12. Continued.</figcaption></figure>

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="4">Bank</th><th colspan="4">Market</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>.271</td><td>.00</td><td></td><td></td><td>-.008</td><td>.11</td><td></td><td></td></tr><tr><td>PrFin(-1)</td><td></td><td>-.410</td><td>.00</td><td>38.6</td><td>PrFin (-1)</td><td>-.240</td><td>.00</td><td>47.3</td><td></td></tr><tr><td>PrFin(-2)</td><td></td><td>-.279</td><td>.00</td><td>(.00)</td><td>PrFin (-2)</td><td>-.117</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>PrEcoC(-1)</td><td>-.553</td><td>-.096</td><td>.10</td><td>4.51</td><td>PrEcoC (-1)</td><td>-.405</td><td>-.279</td><td>.00</td><td>145.5</td></tr><tr><td>PrEcoC(-2)</td><td>(.00)</td><td>.046</td><td>.41</td><td>(.10)</td><td>PrEcoC (-2)</td><td>(.00)</td><td>-.136</td><td>.00</td><td>(.00)</td></tr><tr><td>FL(-1)</td><td>-.658</td><td>-.026</td><td>.00</td><td>11.1</td><td>FL(-1)</td><td>-.472</td><td>.003</td><td>.52</td><td>.813</td></tr><tr><td>FL(-2)</td><td>(.00)</td><td>.013</td><td>.12</td><td>(.00)</td><td>FL(-2)</td><td>(.00)</td><td>.003</td><td>.50</td><td>(.66)</td></tr><tr><td>GDPG(-1)</td><td>-.548</td><td>.002</td><td>.83</td><td>.191</td><td>GDPG(-1)</td><td>-.475</td><td>-.004</td><td>.62</td><td>.822</td></tr><tr><td>GDPG(-2)</td><td>(.00)</td><td>-.003</td><td>.80</td><td>(.90)</td><td>GDPG(-2)</td><td>(.00)</td><td>-.007</td><td>.38</td><td>(.66)</td></tr><tr><td>CACCT(-1)</td><td>-.569</td><td>.001</td><td>.46</td><td>.586</td><td>CACCT(-1)</td><td>-.485</td><td>.001</td><td>.15</td><td>2.05</td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>-.003</td><td>.87</td><td>(.74)</td><td>CACCT(-2)</td><td>(.00)</td><td>.003</td><td>.76</td><td>(.35)</td></tr><tr><td>TOTC(-1)</td><td>.006</td><td>.531</td><td>.00</td><td>96.0</td><td>DCG(-1)</td><td>-.008</td><td>-.029</td><td>.01</td><td>5.62</td></tr><tr><td>TOTC(-2)</td><td>(.00)</td><td>.286</td><td>.00</td><td>(.00)</td><td>DCG(-2)</td><td>(.48)</td><td>-.008</td><td>.49</td><td>(.06)</td></tr><tr><td>KFLOW(-1)</td><td>-.542</td><td>.002</td><td>.53</td><td>.944</td><td>TOTC(-1)</td><td>-.001</td><td>.004</td><td>.92</td><td>.057</td></tr><tr><td>KFLOW(-2)</td><td>(.00)</td><td>.003</td><td>.38</td><td>(.62)</td><td>TOTC(-2)</td><td>(.43)</td><td>-.004</td><td>.89</td><td>(.97)</td></tr><tr><td>REER(-1)</td><td>-.567</td><td>.002</td><td>.00</td><td>48.1</td><td>KFLOW (-1)</td><td>-.470</td><td>.001</td><td>.63</td><td>.448</td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.005</td><td>.13</td><td>(.00)</td><td>KFLOW (-2)</td><td>(.00)</td><td>-.001</td><td>.69</td><td>(.79)</td></tr><tr><td>RIR(-1)</td><td>.043</td><td>1E-5</td><td>.08</td><td>4.231</td><td>M2RES(-1)</td><td>-.492</td><td>.007</td><td>.10</td><td>2.70</td></tr><tr><td>RIR(-2)</td><td>(.00)</td><td>1E-5</td><td>.06</td><td>(.12)</td><td>M2RES(-2)</td><td>(.00)</td><td>-.001</td><td>.77</td><td>(.25)</td></tr><tr><td>PR(-1)</td><td>-.597</td><td>-.002</td><td>.61</td><td>1.33</td><td>RIR(-1)</td><td>-.245</td><td>2E-6</td><td>.53</td><td>4.00</td></tr><tr><td>PR(-2)</td><td>(.00)</td><td>-.006</td><td>.30</td><td>(.51)</td><td>RIR(-2)</td><td>(.00)</td><td>-.7E-6</td><td>.09</td><td>(.13)</td></tr><tr><td>TRADE(-1)</td><td>-.622</td><td>-.002</td><td>.66</td><td>2.31</td><td>PREG(-1)</td><td>-.480</td><td>.016</td><td>.26</td><td>3.67</td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.008</td><td>.15</td><td>(.31)</td><td>PREG(-2)</td><td>(.00)</td><td>.025</td><td>.10</td><td>(.15)</td></tr><tr><td>MONEY(-1)</td><td>-.650</td><td>-.001</td><td>.69</td><td>.755</td><td>PR(-1)</td><td>-.469</td><td>.001</td><td>.00</td><td>14.4</td></tr><tr><td>MONEY(-2)</td><td>(.00)</td><td>.004</td><td>.41</td><td>(.68)</td><td>PR(-2)</td><td>(.00)</td><td>-.001</td><td>.00</td><td>(.00)</td></tr><tr><td>DEBT(-1)</td><td>-.579</td><td>-.002</td><td>.60</td><td>.523</td><td>MONEY(-1)</td><td>-.471</td><td>-.8E-5</td><td>.59</td><td>.320</td></tr><tr><td>DEBT(-2)</td><td>(.00)</td><td>.001</td><td>.52</td><td>(.76)</td><td>MONEY(-2)</td><td>(.00)</td><td>-.3E-5</td><td>.84</td><td>(.85)</td></tr><tr><td>FISCAL(-1)</td><td>-.607</td><td>.006</td><td>.78</td><td>11.4</td><td>DEBT(-1)</td><td>-.473</td><td>.001</td><td>.60</td><td>1.77</td></tr><tr><td>FISCAL(-2)</td><td>(.00)</td><td>-.007</td><td>.00</td><td>(.00)</td><td>DEBT(-2)</td><td>(.00)</td><td>-.002</td><td>.19</td><td>(.41)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>FISCAL(-1)</td><td>-.477</td><td>-.002</td><td>.83</td><td>.348</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>FISCAL(-2)</td><td>(.00)</td><td>-.005</td><td>.59</td><td>(.84)</td></tr><tr><td>C</td><td></td><td>.001</td><td>.56</td><td></td><td></td><td></td><td>-.005</td><td>.80</td><td></td></tr><tr><td>AIC</td><td></td><td>61.1</td><td></td><td></td><td></td><td></td><td>58.0</td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.488</td><td></td><td></td><td></td><td></td><td>.282</td><td></td><td></td></tr><tr><td rowspan="24">Economic crisis</td><td>ECT</td><td></td><td>-.055</td><td>.00</td><td></td><td></td><td>-.026</td><td>.02</td><td></td><td></td></tr><tr><td>PrEcoC(-1)</td><td></td><td>-.754</td><td>.00</td><td>32.5</td><td>PrEcoC (-1)</td><td>-.392</td><td>.00</td><td>34.5</td><td></td></tr><tr><td>PrEcoC(-2)</td><td></td><td>-.422</td><td>.00</td><td>(.00)</td><td>PrEcoC (-2)</td><td>-.174</td><td>.00</td><td>(.00)</td><td></td></tr><tr><td>PrFinC(-1)</td><td>-.002</td><td>.094</td><td>.03</td><td>6.75</td><td>PrFinC (-1)</td><td>.012</td><td>.359</td><td>.00</td><td>45.2</td></tr><tr><td>PrFinC(-2)</td><td>(.11)</td><td>-.013</td><td>.72</td><td>(.03)</td><td>PrFinC (-2)</td><td>(.00)</td><td>.169</td><td>.00</td><td>(.00)</td></tr><tr><td>CPS(-1)</td><td>-.125</td><td>-.001</td><td>.07</td><td>3.18</td><td>Fl(-1)</td><td>-.197</td><td>-.001</td><td>.89</td><td>.055</td></tr><tr><td>CPS(-2)</td><td>(.00)</td><td>7E-5</td><td>.92</td><td>(.20)</td><td>Fl(-2)</td><td>(.00)</td><td>-.001</td><td>.83</td><td>(.97)</td></tr><tr><td>M2RES(-1)</td><td>-.159</td><td>-.001</td><td>.40</td><td>.962</td><td>CPS(-1)</td><td>-.155</td><td>.001</td><td>.00</td><td>48.8</td></tr><tr><td>M2RES(-2)</td><td>(.00)</td><td>.008</td><td>.52</td><td>(.61)</td><td>CPS(-2)</td><td>(.00)</td><td>.001</td><td>.00</td><td>(.00)</td></tr><tr><td>INFL(-1)</td><td>-.009</td><td>.001</td><td>.00</td><td>17.1</td><td>M2RES(-1)</td><td>-.201</td><td>-.001</td><td>.08</td><td>7.14</td></tr><tr><td>INFL(-2)</td><td>(.53)</td><td>4E-5</td><td>.08</td><td>(.00)</td><td>M2RES(-2)</td><td>(.00)</td><td>-.001</td><td>.06</td><td>(.02)</td></tr><tr><td>REER(-1)</td><td>-.159</td><td>.004</td><td>.08</td><td>5.02</td><td>INFL(-1)</td><td>-.006</td><td>7E-6</td><td>.51</td><td>.511</td></tr><tr><td>REER(-2)</td><td>(.00)</td><td>-.006</td><td>.06</td><td>(.08)</td><td>INFL(-2)</td><td>(.04)</td><td>5E-6</td><td>.65</td><td>(.77)</td></tr><tr><td>PR(-1)</td><td>-.082</td><td>-.002</td><td>.00</td><td>22.7</td><td>REER(-1)</td><td>-.130</td><td>-.001</td><td>.74</td><td>1.02</td></tr><tr><td>PR(-2)</td><td>(.00)</td><td>-.001</td><td>.02</td><td>(.00)</td><td>REER(-2)</td><td>(.00)</td><td>-.003</td><td>.36</td><td>(.59)</td></tr><tr><td>TRADE(-1)</td><td>-.160</td><td>.007</td><td>.16</td><td>2.19</td><td>PR(-1)</td><td>-.195</td><td>-.001</td><td>.88</td><td>.245</td></tr><tr><td>TRADE(-2)</td><td>(.00)</td><td>-.003</td><td>.54</td><td>(.33)</td><td>PR(-2)</td><td>(.00)</td><td>-.003</td><td>.64</td><td>(.88)</td></tr><tr><td>POPG(-1)</td><td>-.157</td><td>-.047</td><td>.00</td><td>13.6</td><td>TRADE(-1)</td><td>-.196</td><td>-.001</td><td>.40</td><td>3.00</td></tr><tr><td>POPG(-2)</td><td>(.00)</td><td>-.015</td><td>.25</td><td>(.00)</td><td>TRADE(-2)</td><td>(.00)</td><td>.003</td><td>.12</td><td>(.22)</td></tr><tr><td>GSIZE(-1)</td><td>-.160</td><td>.007</td><td>.01</td><td>6.52</td><td>POPG(-1)</td><td>-.197</td><td>-.018</td><td>.07</td><td>4.41</td></tr><tr><td>GSIZE(-2)</td><td>(.00)</td><td>.001</td><td>.55</td><td>(.03)</td><td>POPG(-2)</td><td>(.00)</td><td>-.013</td><td>.18</td><td>(.10)</td></tr><tr><td>INVEST(-1)</td><td>-.308</td><td>-.022</td><td>.00</td><td>47.8</td><td>GSIZE(-1)</td><td>-.223</td><td>-.002</td><td>.64</td><td>.222</td></tr><tr><td>INVEST(-2)</td><td>(.00)</td><td>-.012</td><td>.00</td><td>(.00)</td><td>GSIZE(-2)</td><td>(.00)</td><td>.005</td><td>.90</td><td>(.89)</td></tr><tr><td>SCHOOL(-1)</td><td>-.168</td><td>-.007</td><td>.43</td><td>2.35</td><td>NVEST(-1)</td><td>-.209</td><td>-.011</td><td>.00</td><td>24.0</td></tr><tr><td>SCHOOL(-2)</td><td>(.00)</td><td>-.001</td><td>.22</td><td>(.30)</td><td>NVEST(-2)</td><td>(.00)</td><td>-.006</td><td>.00</td><td>(.00)</td></tr><tr><td>CACCT(-1)</td><td>-.131</td><td>.009</td><td>.69</td><td>.664</td><td>SCHOOL (-1)</td><td>-.196</td><td>.002</td><td>.77</td><td>.096</td></tr><tr><td>CACCT(-2)</td><td>(.00)</td><td>-.001</td><td>.55</td><td>(.71)</td><td>SCHOOL (-2)</td><td>(.00)</td><td>-.9E-5</td><td>.89</td><td>(.95)</td></tr><tr><td>DCG(-1)</td><td>.030</td><td>-.270</td><td>.00</td><td>28.7</td><td>CACCT(-1)</td><td>-.198</td><td>-.4E-5</td><td>.97</td><td>6.90</td></tr><tr><td>DCG(-2)</td><td>(.00)</td><td>-.155</td><td>.00</td><td>(.00)</td><td>CACCT(-2)</td><td>(.00)</td><td>-.003</td><td>.00</td><td>(.03)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>DCG(-1)</td><td>-.017</td><td>-.017</td><td>.52</td><td>2.56</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>DCG(-2)</td><td>(.00)</td><td>-.032</td><td>.11</td><td>(.27)</td></tr><tr><td>C</td><td></td><td>.003</td><td>.27</td><td></td><td></td><td></td><td>-.003</td><td>.03</td><td></td></tr><tr><td>AIC</td><td></td><td>50.6</td><td></td><td></td><td></td><td></td><td>62.8</td><td></td><td></td></tr><tr><td>R-Squared</td><td></td><td>.32</td><td></td><td></td><td></td><td></td><td>.26</td><td></td><td></td></tr></tbody></table>
<figure><img src="image_55.png" /></figure>

highlights the need for comprehensive policies that address both financial and economic vulnerabilities

The lagged effects of political risk reduction in emergent and bank-based systems, decreasing economic crisis probability in subsequent years, align with research emphasizing the role of governance quality and political stability in economic outcomes (Aisen & Veiga, 2013; Mauro, 1995). This underscores the importance of institutional factors in shaping economic resilience.

In summary, the results from Table 12 contribute to the ongoing discourse on crisis dynamics by providing nuanced insights into the temporal relationships and determinants of financial and economic crises. These findings not only confirm certain patterns observed in earlier works but also introduce new dimensions to our understanding of the complex interactions between economic and financial vulnerabilities. Policymakers and researchers can benefit from these insights in crafting more effective crisis management strategies and policies aimed at fostering long-term economic stability.

Consistent with prior research, our investigation delves into the impact of shocks, whether originating from economic conditions or determinants of financial crises, on the likelihood of crisis occurrence. The impulse response functions divulge noteworthy patterns, shedding light on the endurance and resolution dynamics of financial crises across different economic systems. Echoing insights from earlier studies, our findings suggest that financial crises exhibit resilience and prolonged challenges, particularly in emergent and bank-based systems. Existing research, such as that by Reinhart and Rogoff (2009), has highlighted the prolonged impact of financial crises on economies. In stark contrast, developed and market-based systems tend to experience a more transient duration, with the crisis lasting an average of three years. This underscores the notion that global financial crises manifest persistent characteristics and display negative sensitivity to innovations in the real economic sector. The observed transitory reaction in less regulated environments, where market rules function more effectively, aligns with the regulatory environment's impact on crisis resolution, as highlighted by Babecký et al. (2014).

Economic volatility emerges as a significant factor influencing financial crisis dynamics. In developed and market-based economies, heightened economic volatility acts as a stabilizing force, reducing both short-term and long-term financial crisis probability. This aligns with the idea that increased volatility prompts a more cautious approach among economic agents, fostering stability. This resonates with literature emphasizing the impact of uncertainty on economic agents' behavior. The findings align with studies, such as those by Aisen and Veiga (2013), which underscore the influence of political stability and reduced uncertainty on investment decisions. However, in emerging countries, this stabilizing effect appears transitory, lasting no more than two years. Similarly, the bank-based system, characterized by a highly regulated financial environment, exhibits limited susceptibility to the impact of economic volatility. This is consistent with research highlighting the challenges these economies face in managing and adapting to heightened volatility (Hou & Chen, 2014).

Our analysis reveals that financial crisis vulnerability responds persistently to exchange shocks in the full sample and specifically in emergent and bank-based countries, where these shocks yield positive and statistically significant effects over the long run. This result echoes discussions in the literature on the significance of external factors in shaping financial stability (Frankel & Saravelos, 2012). Moreover, terms of trade volatility in these countries amplify the inclination toward risk-taking, thereby increasing the probability of financial crises. This finding aligns with research emphasizing the role of global economic conditions in shaping crisis dynamics (Hume & Sentance, 2009). In contrast, developed and market-based systems demonstrate a fundamental dependence on liquidity risk, where increased liquidity risk positively influences financial crises. This observation reflects insights from studies that highlight the importance of liquidity conditions in financial stability (Babecký et al., 2014).

The observed differences in crisis dynamics across diverse economic systems have implications for policymakers. Insights from our study suggest that regulatory frameworks and the level of market development play a crucial role in shaping crisis resolution dynamics. Policymakers may draw from these findings to tailor interventions and regulations based on the specific characteristics of their economic system. In conclusion, our study not only aligns with the existing literature on financial and economic crises but also extends our understanding by providing nuanced insights into the varied responses of different economic systems to shocks. The interplay between economic volatility, external shocks, and regulatory environments underscores the complexity of crisis dynamics. These insights are valuable for
<figure><img src="image_56.png" /></figure>

policymakers, economists, and researchers seeking to refine strategies for crisis prevention and resolution in diverse economic contexts.

Figure 3 illustrates noteworthy dynamics in the relationship between economic and financial crises, shedding light on their temporal patterns and mutual influences across different economic systems. Several key observations emerge from the analysis, aligning with and expanding upon insights from prior research. It is evident that, during the initial years, the probability of an economic crisis responds positively to its own deviation. Notably, this effect remains persistent in the long run across all examined samples. The impact of a shock on the probability of an economic crisis is both positive and enduring, albeit diminishing over time. This resonates with literature highlighting the self-reinforcing nature of economic crises (Reinhart & Rogoff, 2009). This finding underscores that, once initiated, economic crises tend to perpetuate themselves over time, impacting the stability of various economic systems. Particularly in developed and market-based systems, a positive shock to the likelihood of a financial crisis immediately heightens the probability of an economic crisis in a sustained manner, whereas this effect is less pronounced in emergent and bank-based systems. This immediate and enduring effect is a notable observation; particularly pronounced in developed and market-based systems, aligning with studies that emphasize the intricate interplay between financial and real sectors in these economies (Babecký et al., 2014). The less significant impact in emergent and bank-based systems suggests varying sensitivities to financial shocks across different economic contexts. Therefore, a shock influencing the volume of credit to the private sector increases the likelihood of an economic crisis over the long term in the overall sample, as well as in developed, emergent, and market-based economies. Similarly, in bank-based countries, an exchange shock significantly amplifies the probability of an economic crisis. Conversely, a positive shock to investment diminishes the likelihood of an economic crisis in most countries. Thus, the findings suggest a sensitivity of the economic situation to financial shocks, highlighting a greater likelihood of a financial crisis preceding an economic crisis. This underscores the interconnectedness of financial and economic variables in line with research emphasizing the role of credit dynamics in shaping economic outcomes (Fielding & Rewilak, 2015). Additionally, the significance of an exchange shock in increasing economic crisis probability in bank-based countries highlights the vulnerability of these economies to external factors, consistent with discussions on global economic linkages (Frankel & Saravelos, 2012).

Furthermore, the study reveals that over the long term, an escalation in the probability of an economic crisis does not exert a substantial impact on the likelihood of a financial crisis. This observation can be elucidated by the informed nature of agents operating in the financial domain, continuously updating their expectations. However, it is crucial to note that the results indicate a detrimental and statistically significant effect of a financial crisis on the real sphere across all samples. This implies that the repercussions of a financial crisis endure and contribute to the socialization of losses, adversely affecting the employment and purchasing power of the most vulnerable agents. This underscores the enduring socio-economic consequences of financial downturns and aligns with broader discussions on the far-reaching implications of financial crises on employment and purchasing power, particularly affecting disadvantaged segments of the population (Reinhart & Rogoff, 2009). In summary, the outcomes underscore the likelihood of a financial crisis preceding an economic crisis and emphasize the enduring negative consequences of financial crises on the real economy. The asymmetry observed, where an increase in the likelihood of an economic crisis does not significantly affect the likelihood of a financial crisis in the long run, suggests a nuanced dynamic between the two spheres. This observation is consistent with the notion that financial markets are more informed and adaptive, potentially reflecting efficient responses to economic conditions (Fernández et al., 2001).

Thus, the findings from Figure 4 contribute to our understanding of the intricate interactions between economic and financial crises, highlighting their persistence, mutual influence, and the lasting impact of financial turmoil on the real economy. These insights have implications for policymakers and stakeholders seeking to develop strategies that address the interconnected challenges posed by crises in diverse economic environments.

In emergent and bank-based economies, particularly over the long term, financial volatility is predominantly influenced by currency volatility, with the latter accounting for more than half of the variance in the probability of a financial crisis, as illustrated in Table 13. This substantial dependence underscores the
<table><caption>Table 13. Continued.</caption><thead><tr><th></th><th>period</th><th>PrFinc</th><th>PrEcoc</th><th>CPS</th><th>M2RES</th><th>INFL</th><th>REER</th><th>PR</th><th>TRADE</th><th>POPG</th><th>GSIZE</th><th>INVEST</th><th>SCHOO</th><th>CACCT</th><th>DCG</th></tr></thead><tbody><tr><td rowspan="10">Economic crisis</td><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>.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>88.2</td><td>5.35</td><td>1.91</td><td>863</td><td>.075</td><td>.138</td><td>677</td><td>.000</td><td>.065</td><td>284</td><td>2.23</td><td>0.40</td><td>0.10</td><td>115</td><td>86.5</td></tr><tr><td>3</td><td>79.9</td><td>6.97</td><td>4.43</td><td>1.74</td><td>1.36</td><td>.641</td><td>926</td><td>.015</td><td>.119</td><td>518</td><td>3.76</td><td>.038</td><td>0.049</td><td>723</td><td>78.3</td></tr><tr><td>4</td><td>74.8</td><td>6.97</td><td>5.56</td><td>1.96</td><td>331</td><td>2.46</td><td>988</td><td>.014</td><td>.119</td><td>702</td><td>4.84</td><td>.034</td><td>0.081</td><td>1.09</td><td>68.3</td></tr><tr><td>5</td><td>70.8</td><td>6.69</td><td>6.00</td><td>2.12</td><td>457</td><td>4.86</td><td>1.01</td><td>.033</td><td>.109</td><td>856</td><td>5.42</td><td>.039</td><td>.151</td><td>1.34</td><td>56.3</td></tr><tr><td>6</td><td>67.3</td><td>6.41</td><td>6.28</td><td>2.28</td><td>505</td><td>7.39</td><td>1.04</td><td>.100</td><td>.983</td><td>5.78</td><td>.057</td><td>.241</td><td>1.53</td><td>43.1</td><td>4.28</td></tr><tr><td>7</td><td>63.9</td><td>6.16</td><td>6.49</td><td>2.42</td><td>527</td><td>9.98</td><td>1.06</td><td>100</td><td>.096</td><td>1.08</td><td>5.98</td><td>.088</td><td>.340</td><td>1.70</td><td>30.7</td></tr><tr><td>8</td><td>60.8</td><td>5.92</td><td>6.64</td><td>2.53</td><td>544</td><td>12.5</td><td>1.07</td><td>1.33</td><td>.096</td><td>1.14</td><td>6.08</td><td>.132</td><td>438</td><td>1.83</td><td>20.7</td></tr><tr><td>9</td><td>57.9</td><td>5.68</td><td>6.73</td><td>2.61</td><td>558</td><td>15.1</td><td>1.08</td><td>1.66</td><td>.099</td><td>1.19</td><td>6.11</td><td>.188</td><td>.534</td><td>1.95</td><td>13.4</td></tr><tr><td>10</td><td>55.3</td><td>5.47</td><td>6.77</td><td>2.67</td><td>569</td><td>17.5</td><td>1.08</td><td>1.97</td><td>.107</td><td>1.23</td><td>6.09</td><td>.254</td><td>624</td><td>2.04</td><td>8.58</td></tr><tr><td rowspan="10">Market</td><td colspan="10">Financial crisis probability</td></tr><tr><td colspan="2">period</td><td>PrFinc</td><td>PrEcoc</td><td>FL</td><td>GDPG</td><td>CACCT</td><td>DCG</td><td>TOTC</td><td>KFLOW</td><td>M2RES</td><td>RIR</td><td>PREG</td><td>PR</td><td>MONEY</td><td>DEBT</td><td>FISCAL</td></tr><tr><td colspan="2">1</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><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td colspan="2">2</td><td>88.7</td><td>9.93</td><td>.021</td><td>.005</td><td>.036</td><td>.067</td><td>.264</td><td>.002</td><td>.086</td><td>.013</td><td>.514</td><td>.282</td><td>.002</td><td>.020</td><td>.017</td></tr><tr><td colspan="2">3</td><td>83.9</td><td>13.3</td><td>.021</td><td>.136</td><td>.234</td><td>.068</td><td>.251</td><td>.030</td><td>.558</td><td>.013</td><td>.920</td><td>.318</td><td>.002</td><td>.087</td><td>.020</td></tr><tr><td colspan="2">4</td><td>81.7</td><td>14.4</td><td>.069</td><td>.182</td><td>.464</td><td>.095</td><td>.285</td><td>.037</td><td>1.03</td><td>.022</td><td>1.11</td><td>.309</td><td>.005</td><td>.125</td><td>.092</td></tr><tr><td colspan="2">5</td><td>80.2</td><td>14.9</td><td>.173</td><td>.188</td><td>.555</td><td>.194</td><td>.306</td><td>.039</td><td>1.38</td><td>.022</td><td>1.24</td><td>.309</td><td>.011</td><td>.150</td><td>.184</td></tr><tr><td colspan="2">6</td><td>79.3</td><td>15.1</td><td>.281</td><td>.187</td><td>.570</td><td>.283</td><td>.312</td><td>.041</td><td>1.68</td><td>.022</td><td>1.35</td><td>.311</td><td>.015</td><td>.167</td><td>.249</td></tr><tr><td colspan="2">7</td><td>78.7</td><td>15.2</td><td>376</td><td>.185</td><td>567</td><td>.325</td><td>.317</td><td>.043</td><td>1.95</td><td>.022</td><td>1.45</td><td>.312</td><td>.017</td><td>.178</td><td>.293</td></tr><tr><td colspan="2">8</td><td>78.2</td><td>15.2</td><td>454</td><td>.185</td><td>5.66</td><td>.345</td><td>.320</td><td>.046</td><td>2.19</td><td>.022</td><td>1.53</td><td>.312</td><td>.018</td><td>.184</td><td>.324</td></tr><tr><td colspan="2">9</td><td>77.8</td><td>15.2</td><td>517</td><td>.184</td><td>5.75</td><td>.357</td><td>.320</td><td>.051</td><td>2.41</td><td>.022</td><td>1.61</td><td>.311</td><td>.019</td><td>.188</td><td>.348</td></tr><tr><td colspan="2">10</td><td>77.5</td><td>15.1</td><td>566</td><td>.184</td><td>5.97</td><td>.364</td><td>.320</td><td>.005</td><td>2.61</td><td>.022</td><td>1.68</td><td>.309</td><td>.020</td><td>.190</td><td>.366</td></tr><tr><td colspan="10">Economic crisis probability</td></tr><tr><td colspan="2">period</td><td>PrEcoc</td><td>PrFinc</td><td>FI</td><td>CPS</td><td>M2RES</td><td>INFL</td><td>REER</td><td>PR</td><td>TRADE</td><td>POPG</td><td>GSIZE</td><td>INVEST</td><td>SCHOO</td><td>CACCT</td><td>DCG</td></tr><tr><td colspan="2">1</td><td>100.0</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><td>.000</td><td>.000</td><td>.000</td><td>.000</td><td>.000</td></tr><tr><td colspan="2">2</td><td>88.5</td><td>4.78</td><td>.116</td><td>5.49</td><td>.168</td><td>.002</td><td>.040</td><td>.022</td><td>.021</td><td>.059</td><td>.007</td><td>.314</td><td>.046</td><td>.002</td><td>.392</td></tr><tr><td colspan="2">3</td><td>82.9</td><td>6.60</td><td>.203</td><td>8.43</td><td>.483</td><td>.175</td><td>.035</td><td>.021</td><td>.018</td><td>.059</td><td>.115</td><td>.292</td><td>.040</td><td>.011</td><td>.521</td></tr><tr><td colspan="2">4</td><td>79.4</td><td>7.60</td><td>.307</td><td>10.0</td><td>7.32</td><td>.372</td><td>.057</td><td>.065</td><td>.037</td><td>.058</td><td>.298</td><td>.261</td><td>.036</td><td>.021</td><td>.605</td></tr><tr><td colspan="2">5</td><td>76.4</td><td>8.36</td><td>.423</td><td>11.3</td><td>.965</td><td>.478</td><td>.088</td><td>.148</td><td>.069</td><td>.071</td><td>.522</td><td>.258</td><td>.036</td><td>.031</td><td>.672</td></tr><tr><td colspan="2">6</td><td>73.9</td><td>8.83</td><td>.539</td><td>12.4</td><td>1.21</td><td>540</td><td>.112</td><td>.238</td><td>.109</td><td>.098</td><td>.786</td><td>.296</td><td>.039</td><td>.042</td><td>.712</td></tr><tr><td colspan="2">7</td><td>71.8</td><td>9.08</td><td>647</td><td>13.3</td><td>1.48</td><td>577</td><td>.128</td><td>.322</td><td>.153</td><td>.135</td><td>1.07</td><td>.381</td><td>.049</td><td>.058</td><td>.731</td></tr><tr><td colspan="2">8</td><td>70.0</td><td>9.17</td><td>744</td><td>14.0</td><td>1.76</td><td>600</td><td>.138</td><td>.391</td><td>.198</td><td>.177</td><td>1.36</td><td>.509</td><td>.065</td><td>.082</td><td>.738</td></tr><tr><td colspan="2">9</td><td>68.4</td><td>9.17</td><td>827</td><td>14.6</td><td>2.04</td><td>613</td><td>.143</td><td>.443</td><td>.242</td><td>.219</td><td>1.64</td><td>.678</td><td>.085</td><td>.116</td><td>.738</td></tr><tr><td colspan="2">10</td><td>67.0</td><td>9.10</td><td>897</td><td>15.0</td><td>2.33</td><td>619</td><td>.146</td><td>.475</td><td>.283</td><td>.256</td><td>1.91</td><td>.882</td><td>.109</td><td>.161</td><td>.733</td></tr></tbody></table>
<figure><img src="image_57.png" /></figure>

A. Full sample

<figure><img src="image_58.png" /></figure>

B. Developed

<figure><img src="image_59.png" /><figcaption>Figure 3. Impulse response functions: financial crisis probability.</figcaption></figure>

prominence of currency-related factors in influencing financial stability consistent with prior research highlighting the pivotal role of currency dynamics in shaping financial conditions, especially in economies characterized by emerging markets and bank-oriented financial systems (Lestano et al., 2003; Babecký et al., 2014). Moreover, the noteworthy contribution of currency volatility, explaining more than half of the variance in the probability of financial crisis, aligns with studies emphasizing the sensitivity of these economies to external shocks, particularly those related to exchange rate fluctuations (Frankel & Saravelos, 2012; Dawood et al., 2017). The exchange rate, as a crucial determinant, becomes a key factor shaping financial vulnerability in these contexts. Following closely is the variance of terms of trade, explaining over 14% of the variation in financial vulnerability within this category of countries. Conversely, in developed and market-based economies, financial volatility is primarily contingent on economic probability and liquidity volatility. For these economies, the reliance of financial volatility on economic probability and liquidity volatility reflects the different dynamics at play in more mature and market-oriented
<figure><img src="image_60.png" /></figure>

C. Emergent

<figure><img src="image_61.png" /></figure>

D. Bank

<figure><img src="image_62.png" /></figure>

E. Market

<figure><img src="image_63.png" /><figcaption>Figure 3. Continued.</figcaption></figure>
<figure><img src="image_64.png" /><figcaption>A. Full sample

B. Developed</figcaption></figure>

<figure><img src="image_65.png" /><figcaption>**Figure 4.** Impulse response functions: economic crisis probability.</figcaption></figure>

financial systems. Economic fundamentals and liquidity considerations take precedence in influencing financial market dynamics in these settings (Fernández et al., 2001; Sala-I-Martin et al., 2004).

Examining the volatility of the real sector, we observe that in emergent and bank-based systems, it is primarily attributed to fluctuations in the exchange rate. In contrast, in developed and market-based systems, the volatility of the real sector is associated with variations in credit to the private sector, with less significance attributed to changes in investment and the volatility of the probability of financial crisis across all categories of countries. This reflects the significance of domestic credit dynamics in influencing real sector conditions (Levine & Zervos, 1998; Beck et al., 1999). This observation leads us to posit that both types of crises are largely shaped by their own preceding developments, especially in the short term, and that this memory effect diminishes over time, allowing other indicators such as the exchange rate to assume greater significance.

Table 14 employing Granger's causality test, establishes noteworthy causal relationships, both unidirectional and bidirectional, among various indicators and the intensity of financial or economic crises. The findings underscore a statistically significant two-way relationship between the probability of financial and economic crises across all types of economies. This implies a robust interaction and a cause-and-effect dynamic between the financial and real spheres in the short term, highlighting the interconnectedness of these domains. For brevity, specific causalities are not exhaustively detailed here, but it's noteworthy that the identified relationships provide insights into the intricate dynamics shaping crises. For instance, in the full sample, the causality
<figure><img src="image_66.png" /></figure>

C. Emergent

<figure><img src="image_67.png" /></figure>

D. Bank

<figure><img src="image_68.png" /></figure>

E. Market

<figure><img src="image_69.png" /><figcaption>Figure 4. Continued.</figcaption></figure>
<figure><img src="image_70.png" /><figcaption>Table 14. Granger causality test¹.</figcaption></figure>

<table><thead><tr><th rowspan="2"></th><th rowspan="2">Variables</th><th rowspan="2">PrFinc</th><th rowspan="2">PrEcoc</th><th rowspan="2">FL</th><th rowspan="2">GDPG</th><th rowspan="2">CACCT</th><th rowspan="2">DCG</th><th rowspan="2">TOTC</th><th rowspan="2">KFLOW</th><th rowspan="2">REER</th><th rowspan="2">RIR</th><th rowspan="2">PR</th><th rowspan="2">TRADE</th><th rowspan="2">MONEY</th><th rowspan="2">DEBT</th><th rowspan="2">FISCAL</th></tr><tr><th>(2E-23)</th><th>(577)</th><th>(2E-5)</th><th>(3E-14)</th><th>(9E-7)</th><th>(4E-8)</th><th>(.002)</th><th>(4E-13)</th><th>(.000)</th><th>(.174)</th><th>(.058)</th><th>(.287)</th><th>(.002)</th></tr></thead><tbody><tr><td rowspan="12">Full sample</td><td>PrFinc</td><td>(9E-23)</td><td>(.017)</td><td>(.042)</td><td>(3E-15)</td><td>(.000)</td><td>(.000)</td><td>(.236)</td><td>(.009)</td><td>(.002)</td><td>(.020)</td><td>(.005)</td><td>(.076)</td><td>(.2E-7)</td><td>(.004)</td><td>(.177)</td></tr><tr><td>PrEcoc</td><td>(1E-9)</td><td>(.012)</td><td>(.044)</td><td>(.002)</td><td>(.000)</td><td>(.149)</td><td>(.049)</td><td>(.158)</td><td>(.064)</td><td>(.171)</td><td>(.064)</td><td>(.171)</td><td>(.383)</td><td>(.1E-6)</td><td>(.018)</td></tr><tr><td>Fl</td><td>(3E-24)</td><td>(.095)</td><td>(.068)</td><td>(.1E-15)</td><td>(.028)</td><td>(.021)</td><td>(.005)</td><td>(.005)</td><td>(.911)</td><td>(.911)</td><td>(.911)</td><td>(.911)</td><td>(.911)</td><td>(.911)</td><td>(.911)</td></tr><tr><td>GDPG</td><td>(3E-5)</td><td>(.003)</td><td>(.056)</td><td>(.1E-21)</td><td>(.028)</td><td>(.021)</td><td>(.002)</td><td>(.002)</td><td>(.763)</td><td>(.008)</td><td>(.008)</td><td>(.008)</td><td>(.768)</td><td>(.1E-5)</td><td>(.003)</td></tr><tr><td>CACCT</td><td>(3E-34)</td><td>(.003)</td><td>(.757)</td><td>(.006)</td><td>(.021)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.763)</td><td>(.008)</td><td>(.008)</td><td>(.008)</td><td>(.768)</td><td>(.1E-5)</td><td>(.003)</td></tr><tr><td>DCG</td><td>(.371)</td><td>(.020)</td><td>(.416)</td><td>(.005)</td><td>(.006)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.671)</td><td>(.385)</td><td>(.401)</td><td>(.336)</td><td>(.884)</td><td>(.000)</td><td>(.006)</td></tr><tr><td>TOTC</td><td>(2E-34)</td><td>(.003)</td><td>(.757)</td><td>(.005)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.763)</td><td>(.008)</td><td>(.008)</td><td>(.008)</td><td>(.768)</td><td>(.1E-5)</td><td>(.003)</td></tr><tr><td>KFLOW</td><td>(1E-28)</td><td>(.001)</td><td>(.785)</td><td>(.1E-15)</td><td>(.013)</td><td>(.333)</td><td>(.002)</td><td>(.002)</td><td>(.763)</td><td>(.008)</td><td>(.008)</td><td>(.008)</td><td>(.768)</td><td>(.1E-5)</td><td>(.003)</td></tr><tr><td>REER</td><td>(8E-5)</td><td>(.001)</td><td>(.785)</td><td>(.1E-15)</td><td>(.013)</td><td>(.333)</td><td>(.002)</td><td>(.002)</td><td>(.763)</td><td>(.008)</td><td>(.008)</td><td>(.008)</td><td>(.768)</td><td>(.1E-5)</td><td>(.003)</td></tr><tr><td>RIR</td><td>(.110)</td><td>(.007)</td><td>(.000)</td><td>(.203)</td><td>(.019)</td><td>(.013)</td><td>(.254)</td><td>(.001)</td><td>(.009)</td><td>(.009)</td><td>(.009)</td><td>(.009)</td><td>(.009)</td><td>(.009)</td><td>(.009)</td></tr><tr><td>PR</td><td>(7E-5)</td><td>(.351)</td><td>(.237)</td><td>(.128)</td><td>(.203)</td><td>(.245)</td><td>(.686)</td><td>(.723)</td><td>(.723)</td><td>(.002)</td><td>(.723)</td><td>(.002)</td><td>(.723)</td><td>(.002)</td><td>(.723)</td></tr><tr><td>TRADE</td><td>(2E-06)</td><td>(.975)</td><td>(.012)</td><td>(.012)</td><td>(.006)</td><td>(.006)</td><td>(.622)</td><td>(.6E-10)</td><td>(.071)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td></tr><tr><td>MONEY</td><td>(.003)</td><td>(.003)</td><td>(.136)</td><td>(.003)</td><td>(.006)</td><td>(.008)</td><td>(.008)</td><td>(.071)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td><td>(.002)</td></tr><tr><td>DEBT</td><td>(.6E-11)</td><td>(.6E-10)</td><td>(.055)</td><td>(.001)</td><td>(.001)</td><td>(.009)</td><td>(.009)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td></tr><tr><td>FISCAL</td><td>(1E-8)</td><td>(.6E-10)</td><td>(.055)</td><td>(.001)</td><td>(.001)</td><td>(.009)</td><td>(.009)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td><td>(.001)</td></tr><tr><td rowspan="12">Developed</td><td>PrFinc</td><td>(3E-22)</td><td>(.671)</td><td>(.453)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td></tr><tr><td>PrEcoc</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.042)</td><td>(.022)</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><td>(.000)</td></tr><tr><td>Fl</td><td>(1E-17)</td><td>(.087)</td><td>(.422)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td><td>(.081)</td></tr><tr><td>GDPG</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>CACCT</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>TOTC</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>KFLOW</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>M2res</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>INFL</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>REER</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>TRADE</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>MONEY</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>DEBT</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td>FISCAL</td><td>(.004)</td><td>(.004)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td><td>(.033)</td></tr><tr><td rowspan="12">Emergent</td><td>PrFinc</td><td>(6E-12)</td><td>(.063)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>PrEcoc</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>Fl</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>GDPG</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>DCG</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>TOTC</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>KFLOW</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>M2res</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>REER</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>RIR</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>PR</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>TRADE</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>MONEY</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>DEBT</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr><tr><td>FISCAL</td><td>(.004)</td><td>(.004)</td><td>(.344)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td><td>(.079)</td></tr></tbody></table>

(Continued)
<figure><img src="image_71.png" /><figcaption>Table 14. Continued.</figcaption></figure>

<table><thead><tr><th rowspan="2">Variables</th><th rowspan="2">PrEcoc</th><th rowspan="2">PrFinc</th><th rowspan="2">CPS</th><th rowspan="2">M2RES</th><th colspan="8">Economic crisis</th></tr><tr><th>INFL</th><th>REER</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 rowspan="10">Developed</td><td>PrEcoc</td><td>(2E-10)</td><td>(.017)</td><td>(.342)</td><td>(.059)</td><td>(.000)</td><td>(.042)</td><td>(.018)</td><td>(.693)</td><td>(.013)</td><td>(.222)</td><td></td><td></td><td></td></tr><tr><td>PrFinc</td><td>(2E-20)</td><td>(.018)</td><td>(.953)</td><td>(.000)</td><td>(3.91)</td><td>(1E-5)</td><td>(8E-15)</td><td>(.326)</td><td>(.5E-6)</td><td>(.103)</td><td></td><td></td><td></td></tr><tr><td>CPS</td><td>(.253)</td><td>(.5E-9)</td><td>(.008)</td><td>(.122)</td><td>(.980)</td><td>(.309)</td><td>(.260)</td><td>(.278)</td><td>(.320)</td><td>(.022)</td><td>(.9E-6)</td><td></td><td></td></tr><tr><td>M2RES</td><td>(.114)</td><td>(.529)</td><td>(.003)</td><td>(.515)</td><td>(.814)</td><td>(.131)</td><td>(.002)</td><td>(.541)</td><td>(.808)</td><td>(.536)</td><td>(.115)</td><td></td><td></td></tr><tr><td>PR</td><td>(.532)</td><td>(.026)</td><td>(.018)</td><td>(.010)</td><td>(.183)</td><td>(.001)</td><td>(.399)</td><td>(.811)</td><td>(.231)</td><td>(.308)</td><td>(.053)</td><td>(.328)</td><td></td></tr><tr><td>TRADE</td><td>(.001)</td><td>(.116)</td><td>(.058)</td><td>(.604)</td><td>(.013)</td><td>(.001)</td><td>(.747)</td><td>(.530)</td><td>(.949)</td><td>(.123)</td><td>(.433)</td><td>(.433)</td><td></td></tr><tr><td>POPG</td><td>(.3E-10)</td><td>(.026)</td><td>(.042)</td><td>(.328)</td><td>(.037)</td><td>(.818)</td><td>(.268)</td><td>(1E-10)</td><td>(.605)</td><td>(.004)</td><td>(.001)</td><td>(.630)</td><td></td></tr><tr><td>GSIZE</td><td>(.000)</td><td>(.5E-18)</td><td>(.000)</td><td>(.328)</td><td>(.054)</td><td>(.001)</td><td>(.001)</td><td>(.592)</td><td>(.605)</td><td>(.043)</td><td>(.003)</td><td>(.368)</td><td>(.308)</td></tr><tr><td>INVEST</td><td>(.407)</td><td>(.428)</td><td>(.062)</td><td>(.168)</td><td>(.107)</td><td>(.131)</td><td>(.849)</td><td>(.2E-7)</td><td>(.624)</td><td>(.010)</td><td>(.336)</td><td>(.575)</td><td>(.575)</td></tr><tr><td>SCHOOL</td><td>(.087)</td><td>(.8E-11)</td><td>(.491)</td><td>(.253)</td><td>(.014)</td><td>(.000)</td><td>(.056)</td><td>(.009)</td><td>(.293)</td><td>(.010)</td><td>(.336)</td><td>(.575)</td><td>(.575)</td></tr><tr><td>CACCT</td><td>(.4E-27)</td><td>(.025)</td><td>(.064)</td><td>(.574)</td><td>(.860)</td><td>(.844)</td><td>(.644)</td><td>(.037)</td><td>(.293)</td><td>(.010)</td><td>(.336)</td><td>(.575)</td><td>(.575)</td></tr><tr><td>DCG</td><td>PrEcoc</td><td>(.4E-17)</td><td>(.025)</td><td>(.064)</td><td>(.574)</td><td>(.860)</td><td>(.844)</td><td>(.644)</td><td>(.037)</td><td>(.293)</td><td>(.010)</td><td>(.336)</td><td>(.575)</td><td>(.575)</td></tr><tr><td rowspan="10">Emergent</td><td>PrFinc</td><td>(1E-7)</td><td>(1.1E-6)</td><td>(1E-5)</td><td>(.172)</td><td>(.005)</td><td>(.042)</td><td>(.716)</td><td>(.309)</td><td>(.254)</td><td>(.2E-7)</td><td>(.222)</td><td>(.222)</td><td>(.222)</td></tr><tr><td>CPS</td><td>(1E-7)</td><td>(6E-21)</td><td>(3E-5)</td><td>(.198)</td><td>(.041)</td><td>(.004)</td><td>(.486)</td><td>(.309)</td><td>(.114)</td><td>(.114)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>M2RES</td><td>(5E-7)</td><td>(.379)</td><td>(.041)</td><td>(.198)</td><td>(.005)</td><td>(.004)</td><td>(.532)</td><td>(.317)</td><td>(.001)</td><td>(.524)</td><td>(.385)</td><td>(.775)</td><td>(.775)</td></tr><tr><td>INFL</td><td>(.001)</td><td>(.8E-18)</td><td>(.129)</td><td>(.005)</td><td>(.005)</td><td>(.000)</td><td>(.000)</td><td>(.000)</td><td>(.001)</td><td>(.524)</td><td>(.385)</td><td>(.775)</td><td>(.775)</td></tr><tr><td>REER</td><td>(.098)</td><td>(.6E-21)</td><td>(.041)</td><td>(.198)</td><td>(.005)</td><td>(.004)</td><td>(.532)</td><td>(.317)</td><td>(.001)</td><td>(.524)</td><td>(.385)</td><td>(.775)</td><td>(.775)</td></tr><tr><td>PR</td><td>(.013)</td><td>(.623)</td><td>(.012)</td><td>(.185)</td><td>(.078)</td><td>(.005)</td><td>(.019)</td><td>(.000)</td><td>(.000)</td><td>(.004)</td><td>(.524)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>TRADE</td><td>(.291)</td><td>(.000)</td><td>(.145)</td><td>(.079)</td><td>(.129)</td><td>(.004)</td><td>(.314)</td><td>(.591)</td><td>(.000)</td><td>(.492)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>POPG</td><td>(.850)</td><td>(.210)</td><td>(.470)</td><td>(.063)</td><td>(.129)</td><td>(.000)</td><td>(.000)</td><td>(.000)</td><td>(.000)</td><td>(.492)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>GSIZE</td><td>(.027)</td><td>(.288)</td><td>(.201)</td><td>(.982)</td><td>(.421)</td><td>(.186)</td><td>(.314)</td><td>(.591)</td><td>(.000)</td><td>(.492)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>INVEST</td><td>(.2E-13)</td><td>(1E-9)</td><td>(.000)</td><td>(.639)</td><td>(.794)</td><td>(.186)</td><td>(.000)</td><td>(.000)</td><td>(.000)</td><td>(.492)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>SCHOO</td><td>(.197)</td><td>(.749)</td><td>(.644)</td><td>(.189)</td><td>(.920)</td><td>(.790)</td><td>(.009)</td><td>(.000)</td><td>(.000)</td><td>(.492)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>CACCT</td><td>(.022)</td><td>(.8E-14)</td><td>(.181)</td><td>(.353)</td><td>(.038)</td><td>(.000)</td><td>(.000)</td><td>(.457)</td><td>(.329)</td><td>(.934)</td><td>(.285)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td>DCG</td><td>(.2E-14)</td><td>(.000)</td><td>(.2E-7)</td><td>(.000)</td><td>(.000)</td><td>(.000)</td><td>(.457)</td><td>(.329)</td><td>(.934)</td><td>(.285)</td><td>(.004)</td><td>(.385)</td><td>(.775)</td></tr><tr><td rowspan="10">Bank</td><td>PrEcoc</td><td>(6E-13)</td><td>(.3E-6)</td><td>(.389)</td><td>(.774)</td><td>(.016)</td><td>(.030)</td><td>(.339)</td><td>(.417)</td><td>(.921)</td><td>(.5E-7)</td><td>(.117)</td><td>(.014)</td><td>(.002)</td></tr><tr><td>PrFinc</td><td>(2E-6)</td><td>(.002)</td><td>(.228)</td><td>(.682)</td><td>(.884)</td><td>(.020)</td><td>(.136)</td><td>(.7E-8)</td><td>(.136)</td><td>(.114)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>CPS</td><td>(.277)</td><td>(.011)</td><td>(.035)</td><td>(.6E-6)</td><td>(.648)</td><td>(.238)</td><td>(.180)</td><td>(.648)</td><td>(.000)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>M2RES</td><td>(3E-7)</td><td>(.072)</td><td>(.000)</td><td>(.648)</td><td>(.000)</td><td>(.000)</td><td>(.651)</td><td>(.549)</td><td>(.000)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>INFL</td><td>(.001)</td><td>(.640)</td><td>(.003)</td><td>(.238)</td><td>(.411)</td><td>(.000)</td><td>(.651)</td><td>(.180)</td><td>(.648)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>REER</td><td>(.656)</td><td>(.012)</td><td>(.000)</td><td>(.651)</td><td>(.000)</td><td>(.000)</td><td>(.651)</td><td>(.549)</td><td>(.000)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>PR</td><td>(.001)</td><td>(.640)</td><td>(.003)</td><td>(.238)</td><td>(.411)</td><td>(.000)</td><td>(.651)</td><td>(.180)</td><td>(.648)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>TRADE</td><td>(.301)</td><td>(.239)</td><td>(.481)</td><td>(.089)</td><td>(.000)</td><td>(.000)</td><td>(.651)</td><td>(.549)</td><td>(.000)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>POPG</td><td>(.000)</td><td>(.172)</td><td>(.157)</td><td>(.250)</td><td>(.008)</td><td>(.000)</td><td>(.651)</td><td>(.180)</td><td>(.648)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>GSIZE</td><td>(.7E-17)</td><td>(.000)</td><td>(.1E-6)</td><td>(.426)</td><td>(.397)</td><td>(.174)</td><td>(.260)</td><td>(.658)</td><td>(.646)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>INVEST</td><td>(.272)</td><td>(.760)</td><td>(.785)</td><td>(.045)</td><td>(.569)</td><td>(.995)</td><td>(.000)</td><td>(.715)</td><td>(.301)</td><td>(.000)</td><td>(.349)</td><td>(.238)</td><td>(.238)</td></tr><tr><td>SCHOO</td><td>(.001)</td><td>(.2E-12)</td><td>(.083)</td><td>(.625)</td><td>(.773)</td><td>(.000)</td><td>(.110)</td><td>(.009)</td><td>(.780)</td><td>(.634)</td><td>(.1E-13)</td><td>(.716)</td><td>(.676)</td></tr><tr><td>CACCT</td><td>(.1E-12)</td><td>(.542)</td><td>(.012)</td><td>(.765)</td><td>(.699)</td><td>(.759)</td><td>(.409)</td><td>(.901)</td><td>(.938)</td><td>(.418)</td><td>(.004)</td><td>(.003)</td><td>(.676)</td></tr><tr><td>DCG</td><td>(.1E-12)</td><td>(.542)</td><td>(.012)</td><td>(.765)</td><td>(.699)</td><td>(.759)</td><td>(.409)</td><td>(.901)</td><td>(.938)</td><td>(.418)</td><td>(.004)</td><td>(.003)</td><td>(.676)</td></tr></tbody></table>

(Continued)
<table><caption>Table 14. Continued.</caption><thead><tr><th rowspan="2">Market</th><th rowspan="2">Variables</th><th colspan="12">Economic crisis</th></tr><tr><th>PrEcoc</th><th>PrFinc</th><th>CPS</th><th>M2RES</th><th>INFL</th><th>REER</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 rowspan="12"></td><td>PrEcoc</td><td>PrEcoc</td><td>PrFinc</td><td>Fl</td><td>(.123)</td><td>(.609)</td><td>(.980)</td><td>(.000)</td><td>(.061)</td><td>(.141)</td><td>(.093)</td><td>(.003)</td><td>(.013)</td><td>(.384)</td><td>(.049)</td><td>(.113)</td></tr><tr><td>PrFinc</td><td>(8E-12)</td><td>(2E-23)</td><td>(1E-6)</td><td>(.248)</td><td>(.000)</td><td>(.378)</td><td>(.043)</td><td>(.034)</td><td>(.407)</td><td>(.094)</td><td>(.000)</td><td>(.8E-10)</td><td>(.801)</td><td>(.792)</td><td>(.537)</td></tr><tr><td>Fl</td><td>(.401)</td><td></td><td></td><td></td><td>(.014)</td><td>(.011)</td><td>(.004)</td><td>(.292)</td><td>(.287)</td><td>(.688)</td><td>(.717)</td><td>(.314)</td><td>(.871)</td><td>(.128)</td><td>(.128)</td></tr><tr><td>CPS</td><td>(9E-16)</td><td>(1E-10)</td><td>(.031)</td><td>(.958)</td><td>(.224)</td><td>(.038)</td><td>(.092)</td><td>(.068)</td><td>(.005)</td><td>(.021)</td><td>(.505)</td><td>(.023)</td><td>(.187)</td><td>(.326)</td><td>(.450)</td></tr><tr><td>M2RES</td><td>(.692)</td><td>(.014)</td><td>(.006)</td><td>(.514)</td><td>(.425)</td><td>(.126)</td><td>(.906)</td><td>(.491)</td><td>(.831)</td><td>(.245)</td><td>(.510)</td><td>(.152)</td><td>(.002)</td><td>(.939)</td><td>(.077)</td></tr><tr><td>INFL</td><td>(.373)</td><td>(.728)</td><td>(.815)</td><td>(.044)</td><td>(.640)</td><td>(.795)</td><td>(.068)</td><td>(.707)</td><td>(.866)</td><td>(.445)</td><td>(.345)</td><td>(.976)</td><td>(.726)</td><td>(.009)</td></tr><tr><td>REER</td><td>(.636)</td><td>(.776)</td><td>(.006)</td><td>(.044)</td><td>(.640)</td><td>(.5E-6)</td><td>(.809)</td><td>(.828)</td><td>(.572)</td><td>(.798)</td><td>(.764)</td><td>(.364)</td><td>(.006)</td><td>(.342)</td></tr><tr><td>PR</td><td>(.391)</td><td>(.115)</td><td>(.076)</td><td>(.003)</td><td>(.019)</td><td>(.001)</td><td>(.033)</td><td>(.103)</td><td>(.732)</td><td>(.899)</td><td>(.104)</td><td>(.857)</td><td>(.2E-5)</td><td>(.505)</td></tr><tr><td>TRADE</td><td>(.390)</td><td>(.142)</td><td>(.061)</td><td>(.893)</td><td>(.738)</td><td>(.277)</td><td>(.103)</td><td>(.732)</td><td>(.899)</td><td>(.756)</td><td>(.197)</td><td>(.770)</td><td>(.655)</td><td>(.727)</td></tr><tr><td>POPG</td><td>(.039)</td><td>(.955)</td><td>(.257)</td><td>(.260)</td><td>(.694)</td><td>(.584)</td><td>(.897)</td><td>(.086)</td><td>(.250)</td><td>(.000)</td><td>(.000)</td><td>(.002)</td><td>(.680)</td><td>(.160)</td></tr><tr><td>GSIZE</td><td>(.000)</td><td>(.953)</td><td>(.037)</td><td>(.266)</td><td>(.699)</td><td>(.278)</td><td>(.912)</td><td>(.046)</td><td>(.132)</td><td>(.005)</td><td>(.2E-5)</td><td>(.583)</td><td>(.325)</td><td>(.471)</td></tr><tr><td>INVEST</td><td>(.4E-6)</td><td>(2E-18)</td><td>(.918)</td><td>(.025)</td><td>(.702)</td><td>(.395)</td><td>(.004)</td><td>(.112)</td><td>(.351)</td><td>(.354)</td><td>(.630)</td><td>(.734)</td><td>(.313)</td><td>(.492)</td></tr><tr><td>SCHOOL</td><td>(.638)</td><td>(.391)</td><td>(.007)</td><td>(.089)</td><td>(.095)</td><td>(.509)</td><td>(.084)</td><td>(.000)</td><td>(.209)</td><td>(.182)</td><td>(.521)</td><td>(.945)</td><td>(.326)</td><td>(.875)</td></tr><tr><td>CACCT</td><td>(.087)</td><td>(.112)</td><td>(.463)</td><td>(.088)</td><td>(.698)</td><td>(.007)</td><td>(.111)</td><td>(.219)</td><td>(.814)</td><td>(.881)</td><td>(.881)</td><td>(.812)</td><td>(.236)</td><td>(.875)</td></tr><tr><td>DCG</td><td>(.3E-6)</td><td>(.602)</td><td>(.199)</td><td>(.207)</td><td>(.610)</td><td>(.001)</td><td>(.298)</td><td>(.933)</td><td>(.893)</td><td>(.984)</td><td>(.881)</td><td>(.812)</td><td>(.236)</td><td>(.875)</td></tr></tbody></table>

Notes: Numbers in this table correspond to p-values.

<figure><img src="image_72.png" /></figure>
<figure><img src="image_73.png" /></figure>

analysis suggests that financial liberalization may lead to a financial crisis, while the reverse relationship is not observed—indicating that financial liberalization does not result from the occurrence of a financial crisis. This finding resonates with literature that has explored the consequences of financial market liberalization. Scholars such as Kaminsky and Reinhart (1999) and Bussiere (2013) have previously discussed the potential risks associated with financial liberalization, highlighting its role in increasing the vulnerability of economies to financial crises. Similarly, the volume of credit to the private sector is identified as a potential cause of economic crises, and economic crises may, in turn, lead to a decline in credit to the private sector.9 This aligns with studies emphasizing the importance of credit dynamics in economic downturns (Easterly & Rebelo, 1993; Levine & Zervos, 1998; Beck et al., 1999).

The overarching conclusion drawn from this analysis is that a range of economic factors can contrib-
ute to the onset of a financial crisis. Economic recession, current account deficits, rapid growth in domes-
tic credit to the private sector, deteriorating terms of trade, exchange rate depreciation, increased real
interest rates, higher levels of commercial openness, reduced liquidity, rising central government debt,
and increased government spending are identified as potential triggers for financial crises. This aligns
with and extends previous research that has explored the multifaceted determinants of financial insta-
bility (Kaminsky & Reinhart, 1999; Alessi & Detken, 2011; Rose & Spiegel, 2011; Frankel & Saravelos, 2012;
Dawood et al., 2017). Furthermore, the results highlight that while capital account liberalization may
contribute to financial crises in various economic contexts, it is not necessarily the predominant factor
triggering such crises. This nuanced understanding provides valuable insights into the relative impor-
tance of different factors in precipitating financial instability, offering policymakers a more refined per-
spective for crisis prevention and management strategies.

By grounding the findings in the context of existing research, the study not only contributes to the empir-
ical understanding of the relationships between economic and financial variables but also enriches the ongo-
ing scholarly dialogue on crisis prediction and management. Policymakers and researchers can leverage these
insights to develop more targeted and effective strategies for crisis prevention and mitigation, taking into
account the multifaceted nature of the relationships between the real and financial spheres.

**3.3.3 Robustness tests**

In the initial phase of our analysis, we considered a comprehensive list of variables, guided by existing litera-
ture, and addressed multicollinearity concerns by excluding variables with high correlation coefficients exceed-
ing 0.5 and variance inflation factors (VIFs) less than 2. Subsequently, through Bayesian Model Averaging
(BMA), we refined the list, eliminating variables deemed less influential in explaining the probability of a
financial crisis. Further refinement involved revisiting the correlation matrix and, based on considerations of
correlation coefficients and VIFs, selectively excluding variables such as 'Fiscal' and 'FL' to construct a more
focused model. This rigorous variable selection process resulted in a final set of 11 candidate variables instead
of 15. Our methodological choices and analytical approaches align with and build upon insights from previ-
ous works in the field of financial and economic crisis literature. The variable selection process, influenced by
correlation coefficients and VIF considerations, mirrors established practices in econometric modeling (Hocking,
1976). By applying Bayesian Model Averaging (BMA) for further refinement, our study aligns with the work of
Fernández et al. (2001), Crespo-Cuaresma and Slacik (2009), and other scholars who advocate for model aver-
aging as a strategy to address challenges in identifying determinants of events.

**FMOLS and DOLS results:** Moving beyond traditional methodologies susceptible to endogeneity issues, such as fixed effects (FE) and generalized method of moments (GMM), our study leveraged dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) to estimate long-term relationships between economic growth and financial crises. Some problems have arisen in these techniques, leading to biased estimates such as regression on panel data with fixed effects not taking into account potential simultaneity, and the GMM technique suffers from the problem of proliferation of instruments as the time dimension increases (De Dominicis et al., 2008). In addition, these techniques are dedicated to the estimation of short-term relationships, which is not our only object of this work, but we are also seeking to find long-term relationships. Recognizing the endogeneity inherent in the relationship between financial and economic conditions, we adopted FMOLS and DOLS as techniques capable of addressing this challenge, as highlighted by Al Mamun et al. (2018) and Risso et al.
<figure><img src="image_74.png" /><figcaption>**Table 15.** FMOLS and DOLS results for the full sample.</figcaption></figure>

<table><thead><tr><th></th><th>Variables</th><th>Coefficient</th><th>Prob.*</th></tr></thead><tbody><tr><td rowspan="15">Financial crisis probability</td><td colspan="3">Dependent variables: Financial crisis probability</td></tr><tr><td>FMOLS</td><td></td><td></td></tr><tr><td>PrEcoc</td><td>.013</td><td>.32</td></tr><tr><td>GDPG</td><td>-.006</td><td>.00</td></tr><tr><td>CACCT</td><td>-.002</td><td>.00</td></tr><tr><td>DCG</td><td>-.050</td><td>.00</td></tr><tr><td>TOTC</td><td>.343</td><td>.00</td></tr><tr><td>KFLOW</td><td>.004</td><td>.01</td></tr><tr><td>REER</td><td>.005</td><td>.00</td></tr><tr><td>RIR</td><td>7E-5</td><td>.00</td></tr><tr><td>PR</td><td>.001</td><td>.15</td></tr><tr><td>MONEY</td><td>-.002</td><td>.00</td></tr><tr><td>DEBT</td><td>5E-5</td><td>.35</td></tr><tr><td>DOLS</td><td></td><td></td></tr><tr><td>PrEcoc</td><td>-.013</td><td>.33</td></tr><tr><td>GDPG</td><td>-.008</td><td>.00</td></tr><tr><td>CACCT</td><td>-.002</td><td>.00</td></tr><tr><td>DCG</td><td>-.047</td><td>.00</td></tr><tr><td>TOTC</td><td>.333</td><td>.00</td></tr><tr><td>KFLOW</td><td>.007</td><td>.00</td></tr><tr><td>REER</td><td>.006</td><td>.00</td></tr><tr><td>RIR</td><td>6E-5</td><td>.00</td></tr><tr><td>PR</td><td>.002</td><td>.04</td></tr><tr><td>MONEY</td><td>-.0002</td><td>.00</td></tr><tr><td>DEBT</td><td>.001</td><td>.09</td></tr><tr><td rowspan="20">Economic crisis probability</td><td colspan="3">Dependent variables: Economic crisis probability</td></tr><tr><td>FMOLS</td><td></td><td></td></tr><tr><td>PrFinc</td><td>.252</td><td>.00</td></tr><tr><td>CPS</td><td>.0001</td><td>.30</td></tr><tr><td>M2RES</td><td>-.001</td><td>.00</td></tr><tr><td>INFL</td><td>.0001</td><td>.00</td></tr><tr><td>REER</td><td>.001</td><td>.00</td></tr><tr><td>PR</td><td>.002</td><td>.00</td></tr><tr><td>TRADE</td><td>-.0002</td><td>.00</td></tr><tr><td>POPG</td><td>.049</td><td>.00</td></tr><tr><td>GSIZE</td><td>.016</td><td>.00</td></tr><tr><td>INVEST</td><td>-.005</td><td>.00</td></tr><tr><td>CACCT</td><td>.012</td><td>.00</td></tr><tr><td>DCG</td><td>-.340</td><td>.00</td></tr><tr><td>DOLS</td><td></td><td></td></tr><tr><td>D(PrFinc)</td><td>.150</td><td>.04</td></tr><tr><td>D(CPS)</td><td>7E-5</td><td>.61</td></tr><tr><td>D(M2RES)</td><td>-.001</td><td>.00</td></tr><tr><td>D(INFL)</td><td>.0001</td><td>.00</td></tr><tr><td>D(REER)</td><td>.001</td><td>.00</td></tr><tr><td>D(PR)</td><td>.002</td><td>.00</td></tr><tr><td>D(TRADE)</td><td>-.0002</td><td>.00</td></tr><tr><td>D(POPG)</td><td>.049</td><td>.00</td></tr><tr><td>D(GSIZE)</td><td>.018</td><td>.00</td></tr><tr><td>D(INVEST)</td><td>-.005</td><td>.00</td></tr><tr><td>D(CACCT)</td><td>.014</td><td>.00</td></tr><tr><td>D(DCG)</td><td>-.332</td><td>.00</td></tr></tbody></table>

(2013). The long-term estimates presented in Table 15 for a panel of 49 developed and emerging countries offer insights into the enduring impacts of financial crises on the real economy.

One noteworthy finding is that, in the long run, an increase in the likelihood of an economic crisis does not significantly impact the likelihood of a financial crisis. This result is rationalized by the notion that agents in the financial sphere are well-informed and continuously update their expectations. However, the study underscores the persistent and detrimental effects of financial crises on the real economy, with statistically significant consequences evident through both FMOLS and DOLS methodologies. This signifies a sustained negative impact on employment and purchasing power, particularly affecting the most vulnerable segments of society. Our findings regarding the persistent and detrimental effects of financial crises on the real economy echo and extend conclusions drawn by various researchers, including those exploring the socialization of losses and the negative repercussions on employment and purchasing power (Reinhart & Rogoff, 2009).

While FMOLS and DOLS provide valuable insights into long-term relationships, the analysis proceeds to employ the Autoregressive Distributed Lag (ARDL) technique to disentangle the total effect into short- and long-term components, offering a more nuanced understanding of the dynamics between economic growth and financial crises. This strategic methodological choice enhances the robustness and depth of
<figure><img src="image_75.png" /></figure>

our investigation. The transition from traditional methodologies like fixed effects (FE) and generalized method of moments (GMM) to more advanced techniques such as ARDL demonstrates an awareness of the limitations of earlier approaches. This evolution in methodology is in line with the broader trend in the literature to employ more sophisticated techniques that capture both short-term and long-term dynamics. The utilization of ARDL provides a nuanced understanding of the temporal aspects of the relationship between economic growth and financial crises.

In summary, our methodological choices and analytical strategies are anchored in the existing literature, reflecting a commitment to building upon established practices and contributing to the refinement and advancement of methodologies in the study of financial and economic crises.

### 3.3.4. Pooled Mean Group (PMG) estimates

3.3.4.1. Financial crisis. In the short run, the likelihood of a financial crisis is influenced by various factors, with a decrease in probability associated with the experience of an economic crisis, positive economic growth, an improvement in the current account balance, and, to a lesser extent, the growth in private sector credit provision (Table 16). The notion of a learning effect resonates with research emphasizing the adaptive behavior of economic agents. Scholars such as Reinhart and Rogoff (2008) have explored the persistence of financial crises and the potential for economies to adapt and mitigate risks over time. The findings align with the idea that a past economic crisis imparts lessons, influencing short-term financial risk perceptions. Conversely, potential triggers for financial crises in the short term include deteriorating terms of trade, substantial capital flows, exchange rate depreciation, and an increase in central government debt. This finds corroboration in studies investigating specific crisis episodes. For instance, studies on currency crises (Krugman, 1979) and sovereign debt crises (Eichengreen et al., 1996) provide insights into the role of these factors in precipitating financial instability. In the long term, the probability of a financial crisis is significantly reduced by experiences of economic crises, economic growth stimulation, current account balance equilibrium, and promoting investment through expanded private sector credit growth. On the other hand, long-term financial crisis likelihood is heightened by deteriorating terms of trade, massive capital inflows, exchange rate depreciation, and an escalation in public debt. This segregation of short-term and long-term effects aligns with the VECM results, reinforcing the presence of a learning effect through economic crisis experiences.

3.3.4.2. Economic crisis. Contrary to earlier findings, an elevated probability of a financial crisis may, in the short run, reduce the likelihood of an economic crisis, a trend that is reversed in the long run. This observation, supported by VECM, FMOLS, and DOLS analyses, indicates that an increase in the likelihood of a financial crisis eventually leads to a higher probability of an economic crisis. This echoes discussions on the intertwined nature of these crises. Claessens et al. (2009) and other scholars have investigated the bidirectional relationships between financial and economic crises, recognizing the potential for a feedback loop where one crisis type exacerbates the other over time. Furthermore, various variables emerge as critical determinants of economic crises, both in the short and long term. Notably, factors such as ensuring market liquidity, fostering increased exchange of goods and services, and promoting higher levels of investment significantly diminish the probability of an economic crisis, as revealed by the empirical analyses. The use of dynamic OLS (DOLS) and fully modified OLS (FMOLS) methods to address endogeneity aligns with the methodological advancements advocated by scholars like Al Mamun et al. (2018) and Risso et al. (2013). These techniques contribute to robust estimates of long-term relationships, offering insights into the enduring consequences of financial crises on the real economy.

Table 17 provides a comprehensive overview of the intricate relationships between the financial and economic situations across various models and time horizons. The utilization of discrete measures to delineate crisis situations and distinguish between short- and long-term effects reveals several noteworthy patterns, adding valuable insights to the existing body of literature. The results highlight a robust and immediate impact of experiencing an economic crisis on reducing the probability of a financial crisis, as indicated by the impulse functions. This aligns with behavioral explanations, suggesting that economic downturns diminish speculative incentives, thereby decreasing the likelihood of financial crises (Kindleberger, 1978). The findings underscore a reciprocal influence between financial and economic spheres, shedding light on the bidirectional causality. An economic shock, according to the Impulse Response functions, swiftly and significantly reduces the likelihood of a financial crisis, possibly reflecting a prudent response by economic agents. Conversely, a financial crisis reinforces caution among economic
<table><caption>**Table 16.** ARDL results.</caption><thead><tr><th></th><th>Variables</th><th>Coef</th><th>Prob.*</th></tr></thead><tbody><tr><td rowspan="24">Pooled Mean Group (PMG) estimates</td><td rowspan="12">Dependent variables: Financial crisis probability</td><td>PrEcoc</td><td>-.040</td><td>.00</td></tr><tr><td>GDPG</td><td>-.006</td><td>.01</td></tr><tr><td>CACCT</td><td>-.008</td><td>.00</td></tr><tr><td>DCG</td><td>-.030</td><td>.00</td></tr><tr><td>TOTC</td><td>.414</td><td>.00</td></tr><tr><td>KFLOW</td><td>.008</td><td>.00</td></tr><tr><td>REER</td><td>.003</td><td>.00</td></tr><tr><td>RIR</td><td>-8E-5</td><td>.42</td></tr><tr><td>PR</td><td>5E-5</td><td>.15</td></tr><tr><td>MONEY</td><td>-8E-6</td><td>.70</td></tr><tr><td>DEBT</td><td>.002</td><td>.00</td></tr><tr><td>Err. Corr. Coef.</td><td>-.256</td><td>.00</td></tr><tr><td rowspan="12">Short Run coefficients</td><td>D(PrFinc (-1))</td><td>-.044</td><td>.29</td></tr><tr><td>D(PrFinc (-2))</td><td>-.079</td><td>.02</td></tr><tr><td>D(PrFinc(-3))</td><td>-.010</td><td>.62</td></tr><tr><td>D(PrEcoc)</td><td>-.062</td><td>.03</td></tr><tr><td>D(GDPG)</td><td>-.006</td><td>.00</td></tr><tr><td>D(CACCT)</td><td>-.001</td><td>.07</td></tr><tr><td>D(DCG)</td><td>-.031</td><td>.04</td></tr><tr><td>D(TOTC)</td><td>.117</td><td>.00</td></tr><tr><td>D(KFLOW)</td><td>.002</td><td>.07</td></tr><tr><td>D(REER)</td><td>.005</td><td>.01</td></tr><tr><td>D(RIR)</td><td>2E-5</td><td>.95</td></tr><tr><td>D(PR)</td><td>.003</td><td>.37</td></tr><tr><td>D(MONEY)</td><td>.004</td><td>.48</td></tr><tr><td>D(DEBT)</td><td>.004</td><td>.05</td></tr><tr><td rowspan="24">Pooled Mean Group (PMG) estimates</td><td rowspan="12">Dependent variables: Economic crisis probability</td><td>PrFinc</td><td>3.90</td><td>.00</td></tr><tr><td>CPS</td><td>.004</td><td>.00</td></tr><tr><td>M2RES</td><td>-.005</td><td>.00</td></tr><tr><td>INFL</td><td>-.002</td><td>.02</td></tr><tr><td>REER</td><td>.001</td><td>.02</td></tr><tr><td>PR</td><td>.001</td><td>.34</td></tr><tr><td>TRADE</td><td>-.001</td><td>.01</td></tr><tr><td>POPG</td><td>.235</td><td>.00</td></tr><tr><td>GSIZE</td><td>.005</td><td>.91</td></tr><tr><td>INVEST</td><td>-.010</td><td>.00</td></tr><tr><td>CACCT</td><td>.028</td><td>.00</td></tr><tr><td>DCG</td><td>1.98</td><td>.00</td></tr><tr><td rowspan="12">Short run coefficients</td><td>Err. Corr. Coef.</td><td>-.002</td><td>.96</td></tr><tr><td>D(PrEcoc (-1))</td><td>-.038</td><td>.03</td></tr><tr><td>D(PrEcoc (-2))</td><td>-.012</td><td>.30</td></tr><tr><td>D(PrFinc)</td><td>-.136</td><td>.02</td></tr><tr><td>D(CPS)</td><td>-5E-5</td><td>.94</td></tr><tr><td>D(M2RES)</td><td>-.005</td><td>.00</td></tr><tr><td>D(INFL)</td><td>.001</td><td>.62</td></tr><tr><td>D(REER)</td><td>-.001</td><td>.36</td></tr><tr><td>D(PR)</td><td>-.001</td><td>.00</td></tr><tr><td>D(TRADE)</td><td>-.001</td><td>.00</td></tr><tr><td>D(POPG)</td><td>-.007</td><td>.66</td></tr><tr><td>D(GSIZE)</td><td>.005</td><td>.00</td></tr><tr><td>D(INVEST)</td><td>-.022</td><td>.00</td></tr><tr><td>D(CACCT)</td><td>.011</td><td>.00</td></tr><tr><td>D(DCG)</td><td>-.298</td><td>.00</td></tr></tbody></table>

agents, contributing to a decline in triggering an economic recession, as evidenced by the P-VECM results. The identified bidirectional causality between the financial and economic spheres corroborates findings from studies exploring the feedback loops between these domains (Minsky, 1982). The quick adaptation of economic agents in response to shocks, as reflected in the Impulse Response functions, echoes the notion of a dynamic interplay between financial and real sectors, contributing to the understanding of short-term dynamics (Bernanke & Gertler, 1989).

When transitioning to a continuous measure of crisis likelihood and accounting for endogeneity, the results diverge. It is observed that the likelihood of an economic crisis significantly increases in countries experiencing a financial crisis, emphasizing the interconnectedness of these crises. Moreover, the enduring impact of a financial shock on economic volatility is notable, suggesting a prolonged influence on economic conditions. This aligns with the recognition in the literature of the multifaceted nature of crisis
<figure><img src="image_76.png" /><figcaption>Table 17. Time varying relationship between various financial crises.</figcaption></figure>

<table><thead><tr><th rowspan="3"></th><th colspan="10">Discrete analysis</th><th colspan="10">Continuous analysis</th></tr><tr><th colspan="2">SE</th><th colspan="2">BMA</th><th colspan="2">P-VECM</th><th colspan="2">Impulse</th><th colspan="2">SE</th><th colspan="2">BMA</th><th colspan="2">P-VECM</th><th colspan="2">Impulse</th><th colspan="2">ARDL</th><th colspan="2">FMOLS</th><th colspan="2">DOLS</th></tr><tr><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th><th>Fcrisis</th><th>Ec crisis</th></tr></thead><tbody><tr><td>Fcrisis</td><td>+</td><td>Y</td><td>-</td><td>N</td><td>-</td><td>Y</td><td>-y</td><td>+Y</td><td>-</td><td>Y</td><td>-</td><td>Y</td><td>-</td><td>Y</td><td>+Y</td><td>-Y</td><td>-Y</td><td>+Y</td><td>-Y</td><td>+Y</td><td>-Y</td><td>+Y</td><td>-Y</td></tr><tr><td>Ecrisis</td><td>-</td><td>N</td><td>-</td><td>Y</td><td>+</td><td>Y</td><td>-y+N</td><td>-</td><td>N</td><td>-</td><td>Y</td><td>-</td><td>Y</td><td>-</td><td>Y</td><td>+N</td><td>-Y</td><td>-Y</td><td>+N</td><td>-Y</td><td>+N</td><td>-Y</td><td>-Y</td></tr></tbody></table>

SE: Simultaneous equation; Y(N) implies that the effect is (is not) statistically significant at the threshold level.
<figure><img src="image_77.png" /></figure>

dynamics (Borio et al., 2001). The consideration of endogeneity in the FMOLS and DOLS models is con-
sistent with recent advancements emphasizing the importance of robust econometric methods to
account for potential biases in estimating causal relationships (Stock & Watson, 2018). While some mod-
els propose a learning effect for financial officers in countries that have undergone economic crises, the
FMOLS and DOLS models, which explicitly consider endogeneity, do not confirm the notion that experi-
encing an economic crisis reduces the likelihood of a financial crisis in the long run. This nuanced finding
highlights the complexity of the relationship and the need for rigorous methodologies that account for
endogenous interactions. The nuanced findings regarding the long-term impact highlight the importance
of distinguishing between short- and long-term effects, an approach supported by studies emphasizing
the persistence of financial and economic shocks (Reinhart & Rogoff, 2009).

The results are in harmony with theoretical literature, notably emphasizing the critical role of the
financial system in influencing economic cycles. Insights from scholars like Fisher (1933) and Bernanke
(1983) are invoked, emphasizing the two-fold impact of the financial accelerator on the real economy
(First, since the borrower's equity is likely procyclical, an additional and persistent source of fluctuation
is introduced to a standard real business cycle. Second, exogenous shocks to the borrower's equity can
trigger economic fluctuations). The asymmetry of the financial accelerator's effect during economic
downturns is particularly emphasized, aligning with the observed sensitivity of the real sphere to finan-
cial sector volatility. The invocation of theoretical underpinnings, including the financial accelerator effect,
draws on a rich tradition of economic thought (Fisher, 1933; Bernanke, 1983). The emphasis on asymme-
try in the financial accelerator effect aligns with research highlighting the varying impact of financial
conditions during different phases of the economic cycle (Kiyotaki & Moore, 1997).

The overall conclusion supports a nuanced interdependence and causality between the real and finan-
cial spheres. This underscores the interconnected nature of financial and economic spheres, resonating
with the literature on systemic risk (Acharya et al., 2010). The sensitivity of the real sphere to financial
sector volatility is accentuated, highlighting the adaptability and learning capabilities of financial agents
in response to economic crises.

**4. Conclusions**

The intricate relationship between financial and economic spheres has been a subject of intense scrutiny, especially in the aftermath of the 2008 financial crisis. The study at hand extends the analysis to 49 emerging and developed countries, covering the period 1984–2016, employing various indicators and estimation techniques to unravel the dynamics between financial and economic crises. The findings, summarized below, bear significant policy implications:

The empirical evidence supports a robust causal relationship between financial and economic spheres.
However, the nature of this relationship exhibits temporal nuances, with the sign of the relationship
varying between short and long terms. This underscores the importance of considering time dynamics
when formulating policies aimed at addressing financial and economic challenges.

The study identifies the exchange rate and terms of trade as primary drivers of volatility in financial markets. Understanding these key determinants can guide policymakers in implementing measures to enhance financial market stability. Policies addressing exchange rate fluctuations and terms of trade shocks may prove effective in mitigating financial volatility.

Volatility in the real sector is primarily explained by the exchange rate, private sector credit levels, and
financial sphere volatility. Policymakers should consider these factors when designing strategies to stabi-
lize the real economy. Managing exchange rate risks and ensuring a balanced approach to private sector
credit may contribute to greater economic resilience.

The study reveals that economic crises tend to be more enduring than financial crises. Policymakers
need to factor in this temporal asymmetry when devising crisis management strategies. Measures
addressing the prolonged impact of economic crises may require sustained policy interventions and sup-
port mechanisms for affected sectors.

One notable finding is the rapid transmission of financial sector difficulties to the real economy,
whereas economic problems are swiftly detected by financial market operators. Policymakers should be
<figure><img src="image_78.png" /></figure>

attuned to this asymmetry, emphasizing the need for prompt and targeted responses to financial sector challenges to prevent their adverse spillover effects on the broader economy.

Given the observed trade-off between crisis onset and financial sector development, policies should focus on redistributing the benefits of economic development across all segments of society. Inclusive economic policies can help mitigate the adverse social impacts of crises.

Policymakers should ensure that the gains from financial development are accompanied by an effective regulatory framework. This is crucial for preventing financial crises and their subsequent impact on the real economy. Striking a balance between financial development and regulatory oversight is imperative.

The study emphasizes the global dimension of prudential regulation. Policymakers should strengthen international coordination in financial regulation to harness the benefits of globally integrated markets while mitigating the risks that could adversely affect the real economy.

The study highlights the importance of learning from the subprime crisis. Policymakers need to carefully implement financial reforms, incorporating lessons from past crises to avoid similar pitfalls. Coordination between macroeconomic and financial policies is paramount for effective crisis mitigation.

Acknowledging the limitations related to the use of annual data, future research could explore more granular data to enhance precision. Additionally, considering the evolving nature of the global economic landscape, periodic updates and expansions of the dataset may provide valuable insights into changing dynamics.

In conclusion, the study's findings offer valuable insights for policymakers navigating the complex terrain of financial and economic interdependence. Crafting policies that address the identified drivers of crises, recognizing temporal dynamics, and fostering global cooperation can contribute to building resilient and sustainable economies in the face of evolving challenges.

## Notes

1. The premium is linked to the additional costs incurred by the creditors to control and verify the results obtained and declared by the borrower.

2. The result of information asymmetry is moral hazard, a situation in which the gain to lenders from a project depends on actions taken by borrowers after the project is initiated and where there is a conflict of interest between lenders and borrowers.

3. For more details on this method see Babecký et al. (2014).

4. Babecký et al. (2014) highlight limits of applying VAR model with dummy variables which explains our choice to go to continuous analysis.

5. The significance of each repressor is weak, positive, or decisive if the PIP lies between 0.5 and 0.75; 0.75 and 0.95; 0.95 and 0.99 or 0.99 and 1, respectively.

6. We implicitly assumed that the financial crisis indicators are the same for developed and emerging countries since the probabilities are calculated using the results of the regression of the overall sample.

7. Similarly, for economic crisis model.

8. Before running regression we test for unit root and cointegration. Our results show that all the series are I (1) and not I (2) which permit performing a cointegration test to establish a potential long run relationship. As made previously we confirm possible cointegration of our series.

9. We supported this type of conclusion based on impulses responses functions (the nature of reaction) that are not presented here.

10. Guidelines for this test: $H_0$: panels contain unit Root; $H_1$: panels are stationary. If p-value is small than 5%, we can reject $H_0$ meaning that we accept alternative hypothesis such as panels are stationary.

11. LTIE: Long Term Individual Effect.

12. Although this variable is significant in explaining financial crisis, we cannot introduce it into our analysis given that it is binary and we cannot affirm its stationarity of order 1.

13. Null Hypothesis: variable in the line does not Granger Cause variable in the column.

14. Peru (1990).

15. Venezuela (2016).

16. Russia (1992).

17. Argentina (1989).

18. Government Stability (12); Socioeconomic Conditions (12); Investment Profile (12); Internal Conflict (12); External Conflict (12); Corruption (6); Military in Politics (6); Religious Tensions (6); Law and Order (6); Ethnic Tensions (6); Democratic Accountability (6); Bureaucracy Quality (4).
<figure><img src="image_79.png" /></figure>

## Acknowledgments

The authors would like to thank the Journal editors and all anonymous referees for their helpful and very constructive comments and their input to improving the research. All errors remain our own.

## Disclosure statement

No potential conflict of interest was reported by the author(s).

## About the authors

**Mekki Hamdaoui** is an Assistant Professor in Economics at the Higher Institute of computer sciences and Management of Kairouan (University of Kairouan, member of the laboratory Modeling, Financing and Economic Development (MOFID-LR21ES28) (University of Sousse), Tunisia. He published in *Cogent Economics and Finance, Health and Quality of Life Outcomes, International Review of Applied Economics, International Economic Journal, International Economics, Journal of Economic Analysis, Journal of Multinational Financial Management, Journal of the Knowledge Economy, Journal of Economic Development, Structural Change and Economic Growth, and SN Business and Economics*. He works in several fields such as economic growth, inequality of opportunity, financial and economic crises, exchange rate policies, and early warning systems.

**Abderraouf Mtiraoui** graduated in Economics from the University of Sousse in Tunisia. Currently, he is the head of the Economics Department at the Private University of Sousse in Tunisia and the Executive Director of the Institute for Advanced Engineering and Research in Tunisia. Since 2012, he participated in various international workshops and conferences in Economics and Financial Development including among others Education, Health, Investment, FDI, Governance, Human Capital, Conventional Finance, Islamic Finance, Political Stability and Entrepreneurship. Furthermore, he is a member of the Research and Innovation Laboratory LAMIDED at the University of Sousse. Thus, he is a reviewer at several international journals namely New Economics Papers, MPRA Paper from the University Library of Munich, Germany, SN Business & Economics (SNBE), the Global Journal of Research in Business Management (GJRBM) and the Journal of Economic Structures.

**Zohra Aroussi** is an academic researcher in Economics at the Faculty of Economic Sciences and Management of Sousse (University of Sousse), Tunisia. She is interested in terrorism and tourism and has published an article in the *Journal of Economic Analysis* concerning determinants of terrorism.

**Mounir Smida** is a Professor in Economics at the Faculty of Economic Sciences and Management of Sousse and director of the laboratory Modeling, Financing and Economic Development (MOFID-LR21ES28) (University of Sousse), Tunisia. He is specialist in monetary economy and published, among others, a book under the title 'The monetary Economy Step by Step'.

## References

* Abadli, R., Kooli, C., & Otmani, A. (2020). Entrepreneurial culture and promotion of exporting in Algerian SMEs: Perception, reality and challenges. *International Journal of Entrepreneurship and Small Business, 41*(2), 227-240.

* Acharya, V. V., Pedersen, L. H., Philippon, T., & Richardson, M. P. (2010). *Measuring systemic risk*. FRB of Cleveland Working Paper No. 10-02. https://ssrn.com/abstract=1595075

* Acemoglu, D., Johnson, S., & Robinson, J. (2002). Reversal of fortune: Geography and institutions in the making of the modern world income distribution. *The Quarterly Journal of Economics*, 117(4), 1231-1294. https://doi.org/10.1162/003355302320935025

* Acemoglu, D. (2009). *Introduction to modern economic growth*. Princeton University Press.

* Aisen, A., & Veiga, F. (2013). How does political instability affect economic growth? *European Journal of Political Economy*, 29, 151-167. https://doi.org/10.1016/j.ejpoleco.2012.11.001

* Allen, F., & Gale, D. (2007). *Understanding financial crises*. Clarendon lecture series in finance. Oxford: Oxford University Press.

* Alessi, L., & Detken, C. (2011). Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity. *European Journal of Political Economy*, 27(3), 520-533. https://doi.org/10.1016/j.ejpoleco.2011.01.003

* Al Mamun, M., Sohag, K., Shahbaz, M., & Hammoudeh, S. (2018). Financial markets, innovations and cleaner energy production in OECD countries. *Energy Economics*, 72, 236-254. https://doi.org/10.1016/j.eneco.2018.04.011

* Al-Raimony, A. (2011). The determinants of economic growth in Jordan. *Abhath Al-Yarmouk, Humanities and Social Sciences Series*, 27(3), 2297-2305.

* Altunbas, Y., Gambacorta, L., & Marques-Ibanez, D. (2009). Securitisation and the bank lending channel. *European Economic Review*, 53(8), 996-1009. https://doi.org/10.1016/j.euroecorev.2009.03.004
<figure><img src="image_80.png" /></figure>

Arusha, C. (2009). Government expenditure, governance and economic growth. *Comparative Economic Studies, 51*(3), 401–418.

Babecký, J., Havránek, T., Matějů, J., Rusnák, M., Šmídková, K., & Vašíček, B. (2014). Banking, debt, and currency crises in developed countries: Stylized facts and early warning indicators. *Journal of Financial Stability, 15*, 1–17. https://doi.org/10.1016/j.jfs.2014.07.001

Barro, R. (1991). Economic growth in a cross-section of countries. *The Quarterly Journal of Economics*, 106(2), 407–443.
https://doi.org/10.2307/2937943

Barro, R. (2003). Determinants of economic growth in a panel of countries. *Annals of Economics and Finance*, 4(2), 231–274.

Beck, T., Levine, R., & Loayza, N. (1999). *Finance and the sources of growth*. World Bank Policy Research Working Paper 2057. World Bank.

Beim, D., & Calomiris, C. (2001). *Emerging financial markets*. Appendix to chapter 1. McGraw-Hill/Irwin Publishers.

Benos, N. (2009). *Fiscal policy and economic growth: Empirical evidence from EU countries*. University of Ioannina. https://mpra.ub.uni-muenchen.de/19174/

Bernanke, B. (1983). Nonmonetary effects of the financial crisis in the propagation of the Great Depression. *American Economic Review, 73*(3), 257–276.

Bernanke, B., & Gertler, M. (1989). Agency costs, net worth, and business fluctuations. *American Economic Review*, 79(1), 14–31.

Bernanke, B., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. In J. B. Taylor & M. Woodford (Eds.), *Handbook of macroeconomics* (Chapter 21, pp. 1341–1393). Elsevier.

Blanchard, O., & Wolfers, J. (2000). The role of shocks and institutions in the rise of European unemployment: The aggregate evidence. *The Economic Journal, 110*(462), C1–C33. https://doi.org/10.1111/1468-0297.00518

Bordo, M., & Haubrich, J. (2010). Credit crises, money and contractions: An historical view. *Journal of Monetary Economics, 57*(1), 1–18. (https://doi.org/10.1016/j.jmoneco.2009.10.015)

Borio, C., Furfine, P., & Lowe, C. (2001). Procyclicality of the financial system and financial stability: Issues and policy options in marrying the macro- and microprudential dimensions of financial stability. *BIS Papers, 1*, 1–57.

Breuer, J. (2004). An exegesis on currency and banking crises. *Journal of Economic Surveys, 18*(3), 293–320. https://doi.org/10.1111/j.0950-0804.2004.00223.x

Bussiere, M. (2013). Balance of payment crises in emerging markets: How early were the 'early' warning signals? *Applied Economics, 459*(12), 1601–1623.

Caballero, R. J., Hoshi, T., & Kashyap, A. K. (2006). *Zombie lending and depressed restructuring in Japan*. NBER Working Paper No. 12129. National Bureau of Economic Research, Inc. http://www.nber.org/papers/w12129

Caprio, G., Jr., & Klingebiel, D. (1996). *Bank insolvencies: Cross country experience*. Policy Research Working Paper, 1620, 1–52. The World Bank.

Caprio, G., & Klingebiel, D. (1997). Bank insolvency: Bad luck, bad policy, or bad banking? In Michael Bruno & Boris Pleskovic (Eds.), *Annual world bank conference on development economics 1996*. World Bank. https://documents1.worldbank.org/curated/fr/467731468767362478/pdf/multi0page.pdf

Céspedes, L. F., Chang, R., & Velasco, A. (2004). Balance sheets and exchange rate policy. *American Economic Review*, 94(4), 1183–1193. https://doi.org/10.1257/0002828042002589

Chang, R., Kaltani, L., & Loayza, N. (2009). Openness is good for growth: The role of policy complementarities. *Journal of Development Economics, 90*(1), 33–49. https://doi.org/10.1016/j.jdeveco.2008.06.011

Chinn, M., & Ito, H. (2018). The Chinn-Ito Index – A de jure measure of financial openness. Now updated to 2016. Portland State University. http://web.pdx.edu/~ito/Chinn-Ito_website.htm

Claessens, S., Klingebiel, D., & Laeven, L. (2005). Crisis resolution, policies, and institutions: empirical evidence. In Daniela Klingebiel & Luc Laeven (Eds.), *Systemic financial crises containment and resolution* (pp. 169–194). Cambridge University Press.

Claessens, S., Kose, M. A., & Terrones, M. E. (2009). What happens during recessions, crunches and busts? *Economic Policy, 24*(60), 653–700. https://doi.org/10.1111/j.1468-0327.2009.00231.x

Claessens, S., Kose, M. A., & Terrones, M. E. (2010). The global financial crisis: How similar? How different? How costly? *Journal of Asian Economics, 21*(3), 247–264. https://doi.org/10.1016/j.asieco.2010.02.002

Corsetti, G., Pesenti, P., & Roubini, N. (1999). Paper tigers? A model of the Asian crisis. *European Economic Review, 43*(7), 1211–1236. https://doi.org/10.1016/S0014-2921(99)00017-3

Crespo-Cuaresma, J., & Slacik, T. (2009). On the determinants of currency crises: the role of model uncertainty. *Journal of Macroeconomics, 31*(4), 621–632. https://doi.org/10.1016/j.jmacro.2009.01.004

Dabrowski, J. J., Beyers, C., & de Villiers, J. P. (2016). Systemic banking crisis early warning systems using dynamic Bayesian networks. *Expert Systems with Applications, 62*(225), 225–242. https://doi.org/10.1016/j.eswa.2016.06.024

Darvas, Z. (2012). Real effective exchange rates for 178 countries: A new database. Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest. Working papers 1201, updated 13 September 2021. https://www.bruegel.org/sites/default/files/wp attachments/WP-2021-15-231221-1.pdf

Dawood, M., Horsewood, N., & Strobel, F. (2017). Predicting sovereign debt crises: An early warning system approach. *Journal of Financial Stability, 28*(C), 16–28. https://doi.org/10.1016/j.jfs.2016.11.008

De Dominicis, L., Florax, R., & de Groot, H. (2008). A meta-analysis on the relationship between income inequality and economic growth. *Scottish Journal of Political Economy, 55*(5), 654–682. https://doi.org/10.1111/j.1467-9485.2008.00470.x
<figure><img src="image_81.png" /></figure>

Dell'Ariccia, G., Detragiache, E., & Rajan, R. (2008). The real effect of banking crises. *Journal of Financial Intermediation*, 17(1), 89-112. https://doi.org/10.1016/j.jfi.2007.06.001

Demirgüc-Kunt, A., & Detragiache, E. (1998). The determinants of banking crises in developing and developed countries. *Staff Papers - International Monetary Fund, 45*(1), 81-109. https://doi.org/10.2307/3867330

Demirgüç-Kunt, A., & Detragiache, E. (2005). Cross-country empirical studies of systemic bank distress: A survey. *National Institute Economic Review*, 192, 68-83. https://doi.org/10.1177/002795010519200108

Demirgüc-Kunt, A., Detragiache, E., & Gupta, P. (2000). *Inside the crisis: An empirical analysis of banking systems in distress*. IMF Working Paper, no. 156. https://www.imf.org/external/pubs/ft/wp/2000/wp00156.pdf

Demirgüc-Kunt, A., Kane, E., & Laeven, L. (2014). *Deposit insurance database, authorized for distribution by Stijn Claessens*. IMF Working Paper. Research Department, WP/14/118. https://www.imf.org/external/pubs/ft/wp/2014/wp14118.pdf

Diamond, D., & Dybvig, P. (1983). Bank runs, deposit insurance, and liquidity. *Journal of Political Economy*, 91(3), 401-419. https://doi.org/10.1086/261155

Domaç, I., & Martinez-Peria, M. (2003). Banking crises and exchange rate regimes: Is there a link? *Journal of International Economics*, 61(1), 41-72. https://doi.org/10.1016/S0022-1996(02)00081-8

Duttagupta, R., & Cashin, P. (2011). Anatomy of banking crises in developing and emerging market countries. *Journal of International Money and Finance*, 30(2), 354-376. https://doi.org/10.1016/j.jimonfin.2010.08.006

Easterly, W., & Rebelo, S. (1993). Fiscal policy and economic growth: an empirical investigation. *Journal of Monetary Economics*, 32(3), 417-458. https://doi.org/10.1016/0304-3932(93)90025-B

Eberly, J., & Krishnamurthy, A. (2014). Efficient credit policies in a housing debt crisis. *Brookings Papers on Economic Activity*, 45(2), 73-136.

Edwards, S. (1992). Trade orientation, distortions and growth in developing countries. *Journal of Development Economics*, 39(1), 31-57. https://doi.org/10.1016/0304-3878(92)90056-F

Eichengreen, B., Rose, A., & Wyplosz, C. (1996). Contagious currency crises: First test. *The Scandinavian Journal of Economics*, 98(4), 463-484. https://doi.org/10.2307/3440879

Fisher, I. (1933). The debt-deflation theory of great depressions. *Econometrica: Journal of the Economic Society*, 1(4), 337-357. https://doi.org/10.2307/1907327

Fouejieu, A. (2017). Inflation targeting and financial stability in emerging markets. *Economic Modelling*, 60(c), 51-70.

Feldkircher, M., & Zeugner, S. (2009). *Benchmark priors revisited: On adaptive shrink-age and the supermodel effect in Bayesian model averaging*. IMF Working Paper No. 09/202. https://www.imf.org/external/pubs/ft/wp/2009/wp09202.pdf

Fernández, C., Ley, E., & Steel, M. F. J. (2001). Model uncertainty in cross-country growth regressions. *Journal of Applied Econometrics*, 16(5), 563-576. https://doi.org/10.1002/jae.623

Fielding, D., & Rewilak, J. (2015). Credit booms, financial fragility and banking crises. *Economics Letters*, 136, 233-236. https://doi.org/10.1016/j.econlet.2015.09.041

Frankel, J., & Saravelos, G. (2012). Can leading indicators assess country vulnerability? Evidence from the 2008-09 global financial crisis. *Journal of International Economics*, 87(2), 216-231. https://doi.org/10.1016/j.jinteco.2011.12.009

Ghosh, S., & Gregoriou, A. (2007). The composition of government spending and growth: Is current or capital spending better? *Oxford Economic Papers*, 60(3), 484-516. https://doi.org/10.1093/oep/gpn005

Giannetti, M. (2007). Financial liberalization and banking crises: The role of capital inflows and lack of transparency. *Journal of Financial Intermediation*, 16(1), 32-63. https://doi.org/10.1016/j.jfi.2006.04.001

Goldfajn, I., & Valdes, R. (1997). *Capital flows and twins crises: The role of liquidity*. International Monetary Fund. WP/97/87.

Gonzalez-Hermozillo, B. (1999). *Determinants of ex-ante banking system distress: A macro-micro empirical exploration of some recent episodes*. IMF Working Paper 99/33.

Gorton, G. (1988). Banking panics and business cycles. *Oxford Economic Papers*, 40(4), 751-781. https://doi.org/10.1093/oxfordjournals.oep.a041885

Guellec, D., & van Pottelsberghe de la Potterie, B. (2001). R&D and productivity growth: panel data analysis for 16 OECD countries. *Oxford Bulletin of Economics and Statistics, OECD Economic Studies*, 33, 103-126. https://www.oecd.org/economy/growth/1958639.pdf

Furceri, D., & Mourougane, A. (2009). *The effect of financial crises on potential output: New empirical evidence from OECD countries*. OECD Economic Department Working Paper No. 699, OECD.

Hamdaoui, M. (2016). Are systemic banking crises in developed and developing countries predictable? *Journal of Multinational Financial Management*, 37-38, 114-138. https://doi.org/10.1016/j.mulfin.2016.09.002

Hamdaoui, M., Ayouni, S. E., & Maktouf, S. (2022). Capital account liberalization, political stability, and economic growth. *Journal of the Knowledge Economy*, 13(1), 723-772. https://doi.org/10.1007/s13132-021-00723-y

Hocking, R. R. (1976). The analysis and selection of variables in linear regression. *Biometrics*, 32(1), 1-49. https://doi.org/10.2307/2529336

Hou, N., & Chen, B. (2014). Military spending and economic growth in an augmented Solow model: a panel data investigation for OECD countries. *Peace Economics, Peace Science and Public Policy*, 20(3), 395-409. https://doi.org/10.1515/peps-2014-0016

Hume, M., & Sentance, A. (2009). The global credit boom: Challenges for macroeconomics and policy. *Journal of International Money and Finance*, 28(8), 1426-1461. https://doi.org/10.1016/j.jimonfin.2009.08.009
<figure><img src="image_82.png" /></figure>

Husain, A. M., Mody, A., & Rogoff, K. (2005). Exchange rate regime durability and performance in developing versus advanced countries. *Journal of Monetary Economics*, 52(1), 35–64. https://doi.org/10.1016/j.jmoneco.2004.07.001

Jemovic, M., & Marinkovic, S. (2021). Determinants of financial crises—An early warning system based on panel logit regression. *International Journal of Financial Economics*, 26(1), 103–117.

Kannan, P. (2012). Credit conditions and recoveries from financial crises. *Journal of International Money and Finance*, 31(5), 930–947. https://doi.org/10.1016/j.jimonfin.2011.11.017

Kaminsky, G., & Reinhart, C. (1999). The twin crises: Causes of banking and balance-of-payments problems. *American Economic Review*, 89(3), 473–500. https://doi.org/10.1257/aer.89.3.473

Kass, R., & Raftery, A. (1995). Bayes factors. *Journal of the American Statistical Association*, 90(430), 773–795. https://doi.org/10.1080/01621459.1995.10476572

Kindleberger, C. (1978). *Manias, panics, and crashes: A history of financial crises*. Basic Books (revised 1989 and 1996). https://delong.typepad.com/manias.pdf

Kiyotaki, N., & Moore, J. (1997). Credit cycles. *Journal of Political Economy*, 105(2), 211–248. https://doi.org/10.1086/262072

Kooli, C., Shanikat, M., & Kanakriyah, R. (2022). Towards a new model of productive Islamic financial mechanisms. *International Journal of Business Performance Management*, 23(1/2), 17–33. https://doi.org/10.1504/IJBPM.2022.119551

Krugman, P. (1979). A model of balance-of-payments crises. *Journal of Money, Credit and Banking*, 11(3), 311–325. https://doi.org/10.2307/1991793

Krugman, P. (2009, September 2). How did economists get it so wrong? *New York Times*. https://www.nytimes.com/2009/09/06/magazine/06Economic-t.html

Kutner, M. H., Nachtsheim, C. J., Neter, J. (2004). *Applied linear regression models* (4th ed.). McGraw-Hill Irwin.

Laeven, L., & Valencia, F. (2020). Systemic banking crises database II. *IMF Economic Review*, 68(2), 307–361. https://doi.org/10.1057/s41308-020-00107-3

Lensink, R., Bo, H., & Sterken, E. (1999). Does uncertainty affect economic growth? An empirical analysis. *Weltwirtschaftliches Archiv*, 135(3), 379–396. https://doi.org/10.1007/BF02707331

Lestano, J. J., Jacobs, J., & Kuper, G. (2003). Indicators of financial crises do work!: An early-warning systems for six Asian countries. In *Mimeo*. Department of Economics, University of Groningen. https://dx. https://doi.org/10.2139/ssrn.480021

Levine, R., & Zervos, S. (1998). Stock markets, banks and economic growth. *American Economic Review*, 26, 1169–1183.

Levy-Yeyati, E. L., & Panizza, U. (2011). The elusive costs of sovereign defaults. *Journal of Development Economics*, 94(1), 95–105. https://doi.org/10.1016/j.jdeveco.2009.12.005

Madigan, D., & Raftery, A. (1994). Model selection and accounting for model uncertainty in graphical models using Occam's window. *Journal of the American Statistical Association*, 89(428), 1535–1546. https://doi.org/10.1080/01621459.1994.10476894

Malmendier, U., & Nagel, S. (2011). Depression babies: Do macroeconomic experiences affect risk taking? *The Quarterly Journal of Economics*, 126(1), 373–416. https://doi.org/10.1093/qje/qjq004

Martin, P., & Rogers, C. A. (2000). Long-term growth and short-term economic instability. *European Economic Review*, 44(2), 359–381. https://doi.org/10.1016/S0014-2921(98)00073-7

Marshall, M., & Jaggers, K. (2007). *Polity IV project: Political regime characteristics and transition, 1800–2006*. Dataset Users' Manual, Center for Systemic Peace. www.systemicpeace.org/polity

Mendoza, E. (2010). Sudden stops, financial crises and leverage. *American Economic Review*, 100(5), 1941–1966. https://doi.org/10.1257/aer.100.5.1941

Minsky, H. (1982). *Inflation, recession and economic policy*. Wheat sheaf Books.

Minsky, H. (1992). *The financial instability hypothesis*. The Jerome Levy Economics Institute Working Paper No. 74. https://doi.org/10.2139/ssrn.161024.

Mishkin, F. S. (1996). *Understanding financial crises: A developing country perspective*. NBER Working Paper N° 5600. National Bureau of Economic Research Inc. https://www.nber.org/system/files/working_papers/w5600/w5600.pdf

Moral-Benito, E. (2011). *Model averaging in economics*. Bank of Spain Working Paper No. 1123. https://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/11/Fich/dt1123e.pdf

Mauro, P. (1995). Corruption and growth. *The Quarterly Journal of Economics*, 110(3), 681–712. https://doi.org/10.2307/2946696

Murphy, K., Shleifer, A., & Vishny, R. (1993). Why is rent-seeking so costly to growth? *American Economic Review*, 84(2), 409–414.

Nguyen, T. C., Wood, J. A., & Castro, V. (2021). *A new comprehensive database of financial crisis: Identification, frequency and duration*. https://doi.org/10.2139/ssrn.3830333.

Nickell, S., Nunziata, L., & Ochel, W. (2005). Unemployment in the OECD since the 1960s: What do we know? *The Economic Journal*, 115(500), 1–27. https://doi.org/10.1111/j.1468-0297.2004.00958.x

Obstfeld, M. (2012). Does the current account still matter? *American Economic Review*, 102(3), 1–23. https://doi.org/10.1257/aer.102.3.1

Pesaran, H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. *Economics Letters*, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
<figure><img src="image_83.png" /></figure>

Pieroni, L. (2009). Military expenditure and economic growth. *Defence and Peace Economics*, 20(4), 327-339. https://doi.org/10.1080/10242690701589876

Pindyck, R. (1988). Irreversible investment, capacity choice and the value of the firm. *American Economic Review*, 78(5), 969-985.

Qin, X., & Luo, C. (2014). Capital account openness and early warning system for banking crises in G20 countries. *Economic Modelling*, 39(C), 190-194. https://doi.org/10.1016/j.econmod.2014.02.037

Raftery, A. E. (1995). Bayesian model selection in social research. *Sociological Methodology*, 25, 111-163. https://doi.org/10.2307/271063

Reinhart, C., & Rogoff, K. (2008). Is the 2007 US sub-prime financial crisis so different? An international historical perspective. *American Economic Review*, 98(2), 339-344. https://doi.org/10.1257/aer.98.2.339

Reinhart, C., & Rogoff, K. (2009). The aftermath of financial crises. *American Economic Review*, 99(2), 466-472. https://doi.org/10.1257/aer.99.2.466

Reinhart, C., & Rogoff, K. (2014). This time is different: A panoramic view of eight centuries of financial crises. *Annals of Economics and Finance*, 15(2), 215-268.

Risso, W., Andrián, L., Punzo, F., & Carrera, E. J. (2013). Economic growth and income distribution in Mexico: A cointegration exercise. *Economic Modelling*, 35, 708-714. https://doi.org/10.1016/j.econmod.2013.08.036

Romer, P. (1990). Endogenous technological change. *Journal of Political Economy*, 98(5, Part 2), S71-S102. https://doi.org/10.1086/261725

Rose, A. K., & Spiegel, M. M. (2011). Cross-country causes and consequences of the 2008crisis: An update. *European Economic Review*, 55(3), 309-324. https://doi.org/10.1016/j.euroecrev.2010.12.006

Rousseau, P., & Wachtel, P. (2000). Equity markets and growth: Cross country evidence on timing outcomes, 1980-1995. *Journal of Banking & Finance*, 24(12), 1933-1957. https://doi.org/10.1016/S0378-4266(99)00123-5

Sala-I-Martin, X., Doppelhofer, G., & Miller, R. (2004). Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. *American Economic Review*, 94(4), 813-835. https://doi.org/10.1257/0002828042002570

Schneider, M., & Tornell, A. (2004). Balance sheet effects, bailout guarantees and financial crises. *Review of Economic Studies*, 71(3), 883-913. https://doi.org/10.1111/j.1467-937X.2004.00308.x

Shera, A., Dosti, B., & Grabova, P. (2014). Corruption impact on economic growth: An empirical analysis. *Journal of Economic Development, Management, IT, Finance and Marketing*, 6(2), 57-77.

Spilimbergo, A., Symansky, S., Blanchard, O., & Cottarelli, C. (2008). *Fiscal policy for the crisis*. IMF Staff Position Note 08/01. Washington: International Monetary Fund. https://www.imf.org/external/pubs/ft/spn/2008/spn0801.pdf

Stock, J. H and., & Watson, M. W. (2018). Identification and estimation of dynamic causal effects in macroeconomics using external instruments. *The Economic Journal*, 128(610), 917-948. https://doi.org/10.1111/ecoj.12593

Sturzenegger, F., & Zettelmeyer, J. (2006). *Debt defaults and lessons from a decade of crises*. MIT Press.

Svensson, J. (2003). Who must pay bribes and how much? *Quarterly Journal of Economics*, 118(1), 207-230.

Tekin, R. (2012). Economic growth, exports and foreign direct investment in least developed countries: A panel granger causality analysis. *Economic Modelling*, 29(3), 868-878. https://doi.org/10.1016/j.econmod.2011.10.013

World Bank. (2002). *Global development finance*. Appendix on Commercial Debt Restructuring. https://documents1.worldbank.org/curated/en/156251468131978934/310436360_20050149094520/additional/multi0page.pdf

Ynikkaya, H. (2003). Trade openness and economic growth: A cross country empirical investigation. *Journal of Development Economics*, 72, 57-89.
<figure><img src="image_84.png" /></figure>

# Appendix A

<table><caption>Table A1. Financial system structure and crises dating (1984–2016).</caption><thead><tr><th rowspan="2">Country</th><th rowspan="2"></th><th rowspan="2">Banking</th><th rowspan="2">Currency</th><th rowspan="2">Sovereign<br>Developed</th><th rowspan="2">Country</th><th rowspan="2"></th><th rowspan="2">Banking</th><th rowspan="2">Currency</th><th rowspan="2">Sovereign<br>Emerging</th></tr><tr><th>Financial<br>structure</th><th>Financial<br>structure</th></tr></thead><tbody><tr><td>Australia</td><td>Market</td><td></td><td></td><td></td><td>Argentina</td><td>Bank</td><td>2001</td><td>1987, 2002, 2013</td><td>2014</td></tr><tr><td>Austria</td><td>Bank</td><td>2008</td><td></td><td></td><td>Brazil</td><td>Market</td><td>1990,<br>1994</td><td>1987,1992, 1999,<br>2015</td><td></td></tr><tr><td>Belgium</td><td>Bank</td><td></td><td></td><td></td><td>Chile</td><td>Market</td><td></td><td></td><td></td></tr><tr><td>Canada</td><td>Market</td><td></td><td></td><td></td><td>China</td><td>Bank</td><td>1998</td><td></td><td></td></tr><tr><td>Denmark</td><td>Market</td><td>2008</td><td></td><td></td><td>Colombia</td><td>Bank</td><td>1998</td><td>1985</td><td></td></tr><tr><td>Finland</td><td>Bank</td><td>1991</td><td>1993</td><td></td><td>Czech<br>Republic</td><td>Bank</td><td>1996</td><td></td><td></td></tr><tr><td>France</td><td>Bank</td><td>2008</td><td></td><td></td><td>Egypt</td><td>Market</td><td></td><td>1990, 2016</td><td>1984</td></tr><tr><td>Germany</td><td>Bank</td><td>2008</td><td></td><td></td><td>Hong Kong</td><td>Market</td><td></td><td></td><td></td></tr><tr><td>Greece</td><td>Market</td><td>2008</td><td></td><td>2012</td><td>Hungary</td><td>Bank</td><td>1991,<br>2008</td><td></td><td></td></tr><tr><td>Ireland</td><td>Market</td><td>2008</td><td></td><td></td><td>India</td><td>Bank</td><td>1993</td><td></td><td></td></tr><tr><td>Israel</td><td>Bank</td><td></td><td>1985</td><td></td><td>Indonesia</td><td>Bank</td><td>1997</td><td>1979, 1998</td><td>1999</td></tr><tr><td>Italy</td><td>Bank</td><td>2008</td><td></td><td></td><td>Korea</td><td>Market</td><td>1997</td><td>1998</td><td></td></tr><tr><td>Japan</td><td>Bank</td><td>1997</td><td></td><td></td><td>Malaysia</td><td>Bank</td><td>1997</td><td>1998</td><td></td></tr><tr><td>Netherlands</td><td>Market</td><td>2008</td><td></td><td></td><td>Mexico</td><td>Market</td><td>1994</td><td>1995</td><td></td></tr><tr><td>New Zealand</td><td>Bank</td><td></td><td>1984</td><td></td><td>Morocco</td><td>Bank</td><td></td><td></td><td></td></tr><tr><td>Norway</td><td>Market</td><td>1991</td><td></td><td></td><td>Pakistan</td><td>Bank</td><td></td><td></td><td></td></tr><tr><td>Portugal</td><td>Bank</td><td>2008</td><td></td><td></td><td>Peru</td><td>Market</td><td></td><td>1988</td><td></td></tr><tr><td>Spain</td><td>Market</td><td>2008</td><td></td><td></td><td>Philippines</td><td>Market</td><td>1997</td><td>1998</td><td></td></tr><tr><td>Sweden</td><td>Market</td><td>1991,<br>2008</td><td>1993</td><td></td><td>Poland</td><td>Market</td><td>1992</td><td></td><td></td></tr><tr><td>Switzerland</td><td>Bank</td><td>2008</td><td></td><td></td><td>Russia</td><td>Market</td><td>1998,<br>2008</td><td>1998, 2014</td><td>1998</td></tr><tr><td>United<br>Kingdom</td><td>Market</td><td>2007</td><td></td><td></td><td>Singapore</td><td>Market</td><td></td><td></td><td></td></tr><tr><td>United States</td><td>Market</td><td>1988,<br>2007</td><td></td><td></td><td>South Africa</td><td>Market</td><td></td><td>1984, 2015</td><td>1985</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Sri Lanka</td><td>Bank</td><td>1989</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Thailand</td><td>Market</td><td>1997</td><td>1998</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Tunisia</td><td>Bank</td><td>1991</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Turkey</td><td>Market</td><td>2000</td><td>1984, 1991, 1996,<br>2001</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td>Venezuela</td><td>Bank</td><td>1994</td><td>1984, 1989, 1994,<br>2002, 2010</td><td>2015</td></tr></tbody></table>

Source: Authors' development based on Laeven and Valencia (2020).
<figure><img src="image_85.png" /><figcaption>Table A2. Data description.</figcaption></figure>

<table><thead><tr><th>Variables</th><th>obs</th><th>Mean</th><th>Std. Dev</th><th>Min</th><th>Max</th><th>Descriptions</th><th>Sources</th></tr></thead><tbody><tr><td>Dependent variables</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Economic crisis</td><td>1617</td><td>.505</td><td>.5001</td><td>0</td><td>1</td><td>A binary variable taking the value 1 in the year of economic recession and 0 otherwise. To construct this variable we used the Hodrick-Prescott filter to separate cyclical component from tendency and considered as recession when the difference between tendency and actual GDP is negative.</td><td>Authors (WDI)</td></tr><tr><td>Precoc</td><td>1617</td><td>.505</td><td>.154</td><td>.028</td><td>.952</td><td>Probability of economic crisis computed based on estimated parmaetrs by logit model</td><td>Authors</td></tr><tr><td>Financial crisis</td><td>1617</td><td>.0507</td><td>.219</td><td>0</td><td>1</td><td>A binary variable taking the value 1 when there is banking, currency of debt crisis and 0 otherwise</td><td>Laeven and Valencia (2020)</td></tr><tr><td>PrFinc</td><td>1617</td><td>.050</td><td>.0844</td><td>.0004</td><td>.999</td><td>Probability of financial crisis based on logit estimations of models parameters</td><td>Authors</td></tr><tr><td>Independent variables</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Determinant of financial crisis</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FL</td><td>1617</td><td>.782</td><td>1.576</td><td>-1.91</td><td>2.35</td><td>It refers to capital account openness based as a measure of external financial liberalization</td><td>Chinn & Ito, 2008, 2014 updated in 2018</td></tr><tr><td>GDPG</td><td>1617</td><td>3.22</td><td>3.77</td><td>-14.5</td><td>25.1</td><td>GDP growth (annual%)</td><td>WDI</td></tr><tr><td>CACCT</td><td>1617</td><td>.164</td><td>5.15</td><td>-14.4</td><td>25.9</td><td>Current Account Balance (%GDP)</td><td>WDI</td></tr><tr><td>DCG</td><td>1617</td><td>.026</td><td>.155</td><td>-.670</td><td>2.87</td><td>Growth rate of domestic credit to the private sector</td><td>WDI</td></tr><tr><td>CPSB</td><td>1617</td><td>70.3</td><td>43.3</td><td>6.884</td><td>214.2</td><td>CPS: credit to the private sector by banks (% of GDP)</td><td>WDI</td></tr><tr><td>TOTC</td><td>1617</td><td>.004</td><td>.096</td><td>-.435</td><td>1.14</td><td>Terms of trade change</td><td>WDI</td></tr><tr><td>KFLOW</td><td>1617</td><td>6.21</td><td>12.5</td><td>-34.9</td><td>156.9</td><td>Capital flow measured by foreign direct investment net inflows and outflows(%GDP)</td><td>WDI</td></tr><tr><td>M2RES</td><td>1617</td><td>13.3</td><td>18.5</td><td>.849</td><td>106.4</td><td>Broad money to total reserves ratio</td><td>WDI</td></tr><tr><td>INF</td><td>1617</td><td>27.3</td><td>226.8</td><td>-8.71</td><td>6261.2<sup>14</sup></td><td>Inflation, GDP deflator (annual %)</td><td>WDI</td></tr><tr><td>REER</td><td>1617</td><td>99.9</td><td>30.47</td><td>20.2</td><td>740.6<sup>15</sup></td><td>Real effective exchange rate index (2010 = 100)</td><td>Darvas (2012) and WDI</td></tr><tr><td>RIR</td><td>1617</td><td>26.7</td><td>502.2</td><td>-1322.3<sup>16</sup></td><td>14178.1<sup>17</sup></td><td>Real lending Interest rate (%)</td><td>WDI and IFS</td></tr><tr><td>PREG</td><td>1617</td><td>.760</td><td>.426</td><td>0</td><td>1</td><td>Political regime quality it corresponds to a Dummy variable taking the value 0 if the country is autocratic and 1 if it is democratic</td><td>Anckar and Fredriksson</td></tr><tr><td>GDPC</td><td>1617</td><td>22447.3</td><td>19510.4</td><td>470.9</td><td>91617.2</td><td>GDP per capita (constant 2010 US$)</td><td>WDI</td></tr></tbody></table>

(Continued)
<figure><img src="image_86.png" /><figcaption>Table A2. Continued.</figcaption></figure>

<table><thead><tr><th>Variables</th><th>obs</th><th>Mean</th><th>Std. Dev</th><th>Min</th><th>Max</th><th>Descriptions</th><th>Sources</th></tr></thead><tbody><tr><td>DINS</td><td>1617</td><td>.720</td><td>.448</td><td></td><td>1</td><td>A dummy variable equals one if the country adopt an explicit deposit insurance and zero otherwise</td><td>Demirgüc-Kunt et al. (2014)</td></tr><tr><td>PR<sup>18</sup></td><td>1617</td><td>70.9</td><td>15.9</td><td>0</td><td>97</td><td>A synthetic index measuring country's political risk as a proxy for governance quality. It contains 12 subcomponents and ranges between 0 and 100 where the higher score points equates to Very Low Risk (high quality of governance and a score of 0 points to Very High Risk (or bad governance quality).</td><td>International Country Risk Guide</td></tr><tr><td>TRADE</td><td>1617</td><td>75.6</td><td>62.9</td><td>12.2</td><td>442.6</td><td>The sum of imports of goods and services and exports of goods and services (% of GDP)</td><td>WDI</td></tr><tr><td>Money</td><td>1617</td><td>74.8</td><td>51.6</td><td>1.82</td><td>376.5</td><td>Broad money (% of GDP)</td><td>WDI</td></tr><tr><td>Debt</td><td>1617</td><td>53.2</td><td>34.3</td><td>1.84</td><td>425.7</td><td>Central government debt, total (% of GDP)</td><td>WDI</td></tr><tr><td>FISCAL</td><td>1617</td><td>74.8</td><td>8.04</td><td>45.2</td><td>95.3</td><td>Fiscal balance corresponding to final consumption expenditure containing private and public spending (% of GDP)</td><td>WDI</td></tr><tr><td>Determinants of economic crisis</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>FL</td><td>1617</td><td>75.080</td><td>47.446</td><td>8.333</td><td>233.2</td><td>Domestic credit to private sector (% of GDP)</td><td>WDI</td></tr><tr><td>CPS</td><td>1617</td><td>75.080</td><td>47.446</td><td>8.333</td><td>233.2</td><td>Domestic credit to private sector (% of GDP)</td><td>WDI</td></tr><tr><td>M2RES</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Population growth (annual %)</td><td>WDI</td></tr><tr><td>INF</td><td>1617</td><td>16.2</td><td>5.00</td><td>2.97</td><td>34.3</td><td>General government final consumption expenditure (% of GDP)</td><td>WDI</td></tr><tr><td>REER</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Population growth (annual %)</td><td>WDI</td></tr><tr><td>PREG</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>General government final consumption expenditure (% of GDP)</td><td>WDI</td></tr><tr><td>PR</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Share of private investment to GDP (Gross capital formation (% of GDP))</td><td>WDI</td></tr><tr><td>TRADE</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Share of private investment to GDP (Gross capital formation (% of GDP))</td><td>WDI</td></tr><tr><td>POPG</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Population growth (annual %)</td><td>WDI</td></tr><tr><td>GSIZE</td><td>1617</td><td>16.2</td><td>5.00</td><td>2.97</td><td>34.3</td><td>General government final consumption expenditure (% of GDP)</td><td>WDI</td></tr><tr><td>INVEST</td><td>1617</td><td>24.0</td><td>5.52</td><td>9.88</td><td>47.8</td><td>Share of private investment to GDP (Gross capital formation (% of GDP))</td><td>WDI</td></tr><tr><td>SCHOOL</td><td>1617</td><td>90.3</td><td>25.3</td><td>18.7</td><td>163.9</td><td>School enrollment, secondary (% net)</td><td>WDI</td></tr><tr><td>CACCT</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>Population growth (annual %)</td><td>WDI</td></tr><tr><td>DCG</td><td>1617</td><td>1.02</td><td>.829</td><td>-1.85</td><td>6.01</td><td>General government final consumption expenditure (% of GDP)</td><td>WDI</td></tr></tbody></table>