rafmacalaba/datause-encoder-data huggingface dataset:
constitutes a global benchmark of each sector’s need for external financing. The authors calculate the external financial dependence ratios by industry using Compustat data on U.S. firms for the years 1980 to 1989. We simply use their data for this measure.

# **Table 1: Definition and source of the variables.**

|Variable|Description|
|---|---|
|Growth|Average annual real growth rate of value added in a particular sector in a particular country<br>over the period 1980 to 1990. The sectors are classified on the basis of ISIC. Source: Rajan<br>and Zingales (1998). Original source: United Nations Database on Industrial Statistics.|
|Growth8097|Average annual real growth rate of value added in a particular sector in a particular country<br>over the period 1980 to 1997, if available. The sectors are classified on the basis of ISIC.<br>Source: Authors’ calculations based on data from the United Nations Database on<br>Industrial Statistics.|
|Share in value added|Fraction of ISIC sector in value added of total manufacturing sector in 1980. Source: Rajan<br>and Zingales (1998).|
|Financial dependence|External financial dependence of U.S. firms by ISIC sector averaged over the period 1980<br>to 1989. Source: Rajan and Zingales (1998).|
|Private credit|Private credit divided by GDP in 1980. Source: Rajan and Zingales (1998).|
|Market cap|Stock market capitalization divided by GDP in 1980. Source: Rajan and Zingales (1998).|
|Total capitalization|Sum of the private credit and stock market capitalization variables.|
|Concentration|Measure of bank concentration. Sum of the market shares measured in total assets of the<br>three largest banks for the period 1989 to 1996, when available. Source: Cetorelli and<br>Gambera (2001).|
|Competition|Measure of bank competition. Average_H_-statistic for the period 1987—1996. Source:<br>Author’s calculations using data from Bankscope and following the methodology in<br>Claessens and Laeven (2004).|
|Accounting|Measure of accounting standards in the country in 1983. Source: Rajan and Zingales<br>(1998).|
|Property rights|Measure of property rights. Median value over 1995—99; score from 1 to 5. A higher score<br>denotes greater protection of property. Source: Heritage Foundation.|
|GDP per capita|The logarithm of GDP per capita in 1980. Source: World Development Indicators of the<br>World Bank.|
|Legal origin|Identifies the legal origin of the company law or commercial code of each country. There<br>are four possible origins: (1) English common law; (2) French commercial code; (3)<br>German commercial code; and (4) Scandinavian commercial code. Source: La Porta et al.<br>(1998).|

<u>Note:</u> This table describes the variables collected for our study. The first column gives the names of the variable as we use it; the second column describes the variable and provides the source from which it was collected.

16
countries. For example, in a precursor program in five Western Balkan countries, Cusolito et al. (2021) found that only 43.7% of firms attended at least one masterclass in-person, and then typically only the one held in their home country.

A final reason for the drop-off in training attendance is that it may have reflected some firms finding the training content less useful than others. Our own impressions from virtually attending the training sessions to observe were that they varied in the dynamism of the instructor, and in the extent to which they provided high-level strategic advice and broad overviews versus specific actionable steps. Some firms noted they either found some of the content too broad, not directly applicable to their business, or to be covering things they were already doing. However, even when content was somewhat familiar, several firms noted that it helped affirm that they were on the right track, or spurred them to get around to implementing practices they knew they should be doing but had not yet implemented. They also noted the one-on-one sessions had been helpful in addressing firm-specific issues. Firms showed most interest in improving customers and markets, and so were less likely to attend one-on-one sessions later in the program that were intended to focus on other business aspects such as financial performance. Only 9% of treated firms said the program had not been useful for their business, with 45% saying it was somewhat useful, and 46% very useful. Overall, 81% of treated firms said the program met or exceeded their expectations, and 90% would recommend it to other firms like theirs. The control group was less satisfied with the program, with only 27% saying it had been very useful to their firm, and 35% saying it did not meet their expectations.

# **3 Results**

## **3.1 Data collection and attrition**

Our baseline data come from the application form and diagnostic sheets submitted by all firms as they entered the program. Administrative data from the program provide the data on attendance used in our take-up analysis above. We then have three sources of follow-up data to measure outcomes of participating in the program. The first are the scores from judges, based on the pitch decks and traction sheets submitted by firms at the end of May 2021. The purpose of these judge scores were to identify the firms that were most ready to represent the region in front of investors. They are only available for 136 out of the 225 firms (60.4%), and capture a measure of investment readiness of the firm seven months after the program started. The judges were a mix of investors and experts in small and medium enterprise growth in the region, and were blinded to treatment status. The judges gave firms a score out of 5 for seven different categories, with pre-assigned weights then used to arrive at a total score: unique value proposition (20%), technology (10%), business model (10%), team (10%), traction (30%), market expansion (10%) and finally pitch deck effectiveness 11
WPS 3288

**Is There Room for Foreign Exchange Interventions under an Inflation Targeting Framework?**

**Evidence from Mexico and Turkey**

by

**Ilker Domaç**<sup>†</sup> **and Alfonso Mendoza**<sup>‡</sup>

# **Abstract**

The salient characteristics of emerging market economies coupled with the increasing adoption of inflation targeting in these countries has stimulated much debate about the role of the exchange rate in inflation targeting regimes. The paper aims at shedding more light on this issue by investigating whether central bank foreign exchange interventions have had any impact on the volatility of the exchange rate in Mexico and Turkey since the adoption of the floating regime. To this end, the study, using daily data on foreign exchange intervention, employs an Exponential GARCH framework. Empirical results suggest that both the amount and frequency of foreign exchange interventions have decreased the volatility of the exchange rates in these countries. The findings corroborate the notion that if foreign exchange interventions are carried out with finesse and sensibly—i.e., not to defend a particular exchange rate—they could play a useful role under an inflation targeting framework in containing the adverse effects of temporary exchange rate shocks on inflation and financial stability.

**_Keywords_ :** Inflation targeting; exchange rate volatility; central bank intervention; E-GARCH.

**JEL** **_classification_** : C32; E58; F31; G15

# World Bank Policy Research Working Paper 3288, April 2004

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> † Corresponding author. The World Bank. Email: idomac@worldbank.org.

> ‡ University of York **.** Email: amv101@york.ac.uk.
And last, how much would such an intervention cost in terms of dollars per life-year saved and what does this imply in terms of cost-effectiveness?<sup>4</sup> To answer these questions, we analyze 38 developing countries where recent Demographic and Health Surveys (DHS) are available. Building on a previous paper (Günther and Fink, 2010) we first estimate a logistic model to quantify the effect of improved water and sanitation on child mortality. Based on the estimated relation between water, sanitation and child mortality, we compute counterfactual child mortality rates under various water and sanitation improvement scenarios in a second step. In a third step, we compare the predicted mortality changes to the country-specific child mortality goals set in MDG 4. In a last step, we price the infrastructure investment needed for each of the relevant scenarios, and calculate country-specific estimates of cost per life-year saved.

Our empirical estimates suggest that, on average, access to “basic” improved water and sanitation technology (such as public water pumps and ventilated improved pit latrines) lowers child mortality by 8 deaths per 1000 children born, while high-end technologies as private water connections and flush toilets lead to an average mortality reduction of 25 deaths per 1000 live births.<sup>5</sup> Compared to the current gap between child mortality and the 2015 mortality targets this implies that basic improved water and sanitation could on average reduce the gap by about 13 percent, while private piped water and flush toilets would reduce the mortality gap by about 41 percent. Given the high degree of heterogeneity across countries in terms of current infrastructure and child mortality, the variations in the potential progress towards achieving MDG 4 are substantial across regions and countries.

Our calculations show that the cost associated with water and infrastructure improvements is substantial in absolute terms, but not necessarily large when compared to the number of lifeyears saved. Across all Sub-Saharan African countries, we estimate the average cost per lifeyear saved at around US$ 1000, with similar estimates for basic technologies and household water connections and flush toilets. Even though piped water and connected toilets are much more expensive than low-tech technologies, the average cost per life-year saved turns out to be roughly the same due to the longer durability and superior health impact associated with the higher-end technologies.

> 4 In this study we only analyze the total mortality effect of improved water and sanitation infrastructure, but exclude morbidity and nutrition effects that might have long-term consequences for schooling outcomes, laborforce productivity and hence lifetime earnings. Our cost benefit analysis therefore only takes into account lifeyears saved, following a pure health perspective.

> 5 For a detailed definition of improved water and sanitation technology see Table 2.

4
and its prediction of thrombolysis decisions for black and white patients,” _Journal of general internal medicine_ , 2007, _22_ (9), 1231–1238.

- **Greenwald, Anthony G and Brian A Nosek** , “Statistically Small Effects of the Implicit Association Test Can Have Societally Large Effects,” _Journal of Personality and Social Psychology_ , 2015, _108_ (4), 553–561.

- **Greenwald, Anthony G., Brian A. Nosek, and Mahzarin R. Banaji** , “Understanding and Using the Implicit Association Test: I. An Improved Scoring Algorithm,” _Journal of Personality and Social Psychology_ , 2003, _85_ (2), 197–216.

- **Karpinski, Andrew and James L Hilton** , “Attitudes and the Implicit Association Test,” _Journal of Personality and Social Psychology_ , 2001, _81_ (5), 774–788.

- **Lowes, Sara, Nathan Nunn, James A. Robinson, and Jonathan Weigel** , “Understanding ethnic identity in Africa: Evidence from the Implicit Association Test (IAT),” _American Economic Review_ , 2015, _105_ (5), 340–345.

- **McConnell, Allen R. and Jill M. Leibold** , “Relations among the Implicit Association Test, Discriminatory Behavior, and Explicit Measures of Racial Attitudes,” _Journal of_ –

- _Experimental Social Psychology_ , 2001, _37_ (5), 435 442.

- **Meade, Adam W.** , “FreeIAT: An open-source program to administer the implicit association test.,” _Applied Psychological Measurement_ , 2009, _33_ (643), 2003.

- **Poehlman, T. Andrew, Eric Luis Uhlmann, Anthony G. Greenwald, and Mazharin R. Banaji** , “Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity.,” _Journal of personality and social psychology_ , 2009, _97_ (1), 17–41.
|Asuncion Sewerage Project|Ventura Bengoechea|
|---|---|
|Asuncion Sewerage Project|Ventura Bengoechea|
|Asuncion Sewerage Project|Ventura Bengoechea|
|Asuncion Sewerage Project|Ventura Bengoechea|
|Asuncion Sewerage Project|Ventura Bengoechea|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|PY-Maternal Health and Child Development Project|Montserrat Meiro-Lorenzo|
|National Trust Fund for Protected Areas(GEF)|Pierre Werbrouck|
|Lima - Amazon Transport Corridor Project||
|Irrigation Rehabilitation Project||
|Irrigation Rehabilitation Project||
|Puno Rural Development Project||
|Puno Rural Development Project||
|Puno Rural Development Project||
|Irrigation Rehabilitation Project(02)Lower Piura||
|Irrigation Rehabilitation Project(02)Lower Piura||
|Irrigation Rehabilitation Project(02)Lower Piura||
|Petroleum Production Rehabilitation Project||
|Petroleum Production Rehabilitation Project||
|Bayovar Phosphate Engineeringand Technical Assistance Project||
|Bayovar Phosphate Engineeringand Technical Assistance Project||
|Industrial Credit Project(02)||
|Industrial Credit Project(02)||
|Industrial Credit Project(02)||
|Industrial Credit Project(02)||
|Technical Assistance Project - Siderperu||
|Power EngineeringProject||
|Power EngineeringProject||
|Power EngineeringProject||
|Aviation Development Project||
|Aviation Development Project||
|Aviation Development Project||
|Aviation Development Project||
|Agricultural Research and Extension Project||
|Agricultural Research and Extension Project||
|Agricultural Research and Extension Project||
|Agricultural Research and Extension Project||
|Small Scale Enterprise Project||
|Small Scale Enterprise Project||
|Small Scale Enterprise Project||
Policy Research Working Paper 10580

# **Abstract**

Using three rounds of the World Bank’s Business Pulse Surveys in South Asia, this paper quantifies the relationship between informality and firms’ investment and employment decisions. Accounting for multidimensionality in definition and the margins of informality, the analysis suggests that _first_ , informal firms remain credit and liquidity constrained before and during the crisis, especially the necessity firms. In the pre-crisis period, access to finance is correlated with the extensive margin of informality, while during the crisis, both margins of informality matter. _Second_ , informal firms perceive uncertainty to be higher because of pessimistic expectations on recovery and lower ability to predict future sales, especially the necessity firms. _Third_ , credit constraints and accentuated uncertainty among informal firms discourage investments. _Finally_ , while employment growth is slow and gradual for formal firms as they begin to recover sales, job growth in informal firms does not correspond to the recovery. The results suggest that countries with a large informal sector may face unusually depressed investments and jobs recovery and may have to deploy additional policy levers to accelerate recovery in the post-crisis period.

This paper is a product of the International Finance Corporation and the Office of the Chief Economist, South Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http:// www.worldbank.org/prwp. The authors may be contacted at agrover1@ifc.org and mpereiralopez@ifc.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Along with 10 other countries, including all other Nordic countries, Sweden has no legal requirement for severance payments. In Sweden collective bargaining agreements provide for fee-based insurance schemes, funded by employer contributions. Employers therefore do not need to provide a severance package when making a worker redundant. These insurance schemes, viewed as best practice by the OECD, ease the cost of redundancy for employers while ensuring that workers receive some compensation after their employment ends (World Bank, 2014). The average severance payment is 5.2 weeks of salary in the EU15, 3.5 in the G7 and 0 in the Nordic region (Table 4).

Data combining the mandatory notice period and severance payment into the overall cost of redundancy, as published in the World Economic Forum’s _Global Competitiveness Report 2014,_ show that Sweden has the sixth highest cost in the sample, at 14.4 weeks of salary (Figure 9). This surpasses the averages for the OECD (12.9), EU15 (12.1), G7 (9.1) and other Nordic countries (7.2). Portugal has the highest redundancy cost, at 23.1 weeks of salary, followed by Luxembourg (21.7) and Germany (21.6). Denmark and the United States have no redundancy cost.

# **_Implications for policy_**

All in all, the data on redundancy regulations from the OECD and Doing Business reveal that some aspects of redundancy rules in Swedish labor law are much stricter than those in some comparator economies. These include a longer notice period, priority rules applying for dismissals and reemployment and a requirement to retrain redundant workers before they can be dismissed. Another important issue is that Sweden’s redundancy regulations provide strong protection for permanent employees at the expense of temporary employees, increasing the risk of a fragmented labor market in which permanent employees enjoy high security and promising job prospects while temporary employees are largely marginalized.

Because rigid redundancy regulations and dual labor markets have been shown to impose significant costs on the economy, these issues may need the urgent attention of policy makers. One recommendation that resonates in the recent literature is to equalize the redundancy regulations for all types of contracts at a lower level. But relaxing redundancy regulations for all employees without appropriate measures to protect the unemployed may not be compatible with the Swedish tradition of strong solidarity and social awareness. A possible solution is offered by Denmark’s flexicurity model, which makes it easy to dismiss an employee but provides a strong safety net for the unemployed through unemployment insurance. The flexicurity model essentially combines three policies: flexible hiring and redundancy rules, a generous social safety net and active labor market policies (Andersen, 2012). This model has already been implemented in Sweden to a certain extent and thus could be further explored and developed to address the current issues in the country’s labor market.

21
(ρ��0.46), GDP growth (ρ��0.10) and child mortality (ρ��0.24). Hence, we expect that the percentage of _suffering_ individuals is closely related to perceived hardship and grievances and hence has a direct effect on nonviolent resistance. In the regressions, we control for the percentage of people who report to be _struggling_ and therefore may also be experiencing considerable hardship.

_Table 1 Countries with the lowest and highest percentage of citizens who report to be 'suffering'_ according to the Gallup World Poll (2005-2015)

|Countries with lowest incide<br>|nce of suffering<br>|Countries with highest incidence of suffering<br><br>|
|---|---|---|
|Country|Suffering|Country<br>Suffering|
|Norway|1.2|Bulgaria<br>39.1|
|Denmark|1.3|Afghanistan<br>34.9|
|Canada|1.6|Burundi<br>34.5|
|Netherlands|1.7|Haiti<br>32.5|
|United Arab Emirates|1.8|South Sudan<br>32.5|
|New Zealand|1.8|Armenia<br>29.2|
|Switzerland|1.8|Tanzania<br>29.0|
|Sweden|1.8|Yemen,Rep.<br>28.5|
|Oman|2.0|Hungary<br>26.7|
|Luxembourg|2.0|Georgia<br>26.7|
|Australia|2.1|Serbia<br>25.9|
|Brazil|2.3|Ukraine<br>25.8|

Table 1 lists those countries with the lowest and highest percentages of suffering people.

Not surprisingly, most of the countries with the lowest percentage of _suffering_ individuals are high-income economies, whereas those with the highest percentage of _suffering_ individuals are low-income economies, most of which are fragile countries. Bulgaria and, to a lesser extent, Serbia stand out among the group of countries with the highest percentage of suffering people. Both countries report a very high percentage of _suffering_ individuals, which is difficult to explain using objective economic indicators alone.<sup>8</sup>

> 8 Sardamov (2007) argues that the level of suffering in Bulgaria can largely be explained by unrealistically high expectations for development and a general distrust in public institutions.

13