rafmacalaba/datause-encoder-data huggingface dataset:
1 if financial liberalization had occurred in the previous 5 years and 0 otherwise.<sup>6</sup> To ease interpretations, we report the effects of one-unit changes in the dependent variables on the probability of a crisis (expressed in percentage points) evaluated at the mean value of the data. We also report the associated z-statistics that test the null hypothesis of no effect.

The first column in table 3 presents results of a probit model where the dependent variable takes the value of 1 during years with a financial crises and 0 otherwise (excluding 5 years after the crises starts or while the crises last). The macroeconomic variables have the expected signs and are significant except for the growth rate of terms of trade and the claims of the private sector as a share of GDP. In this specification, the probability of a crisis increases both in the 5 years following liberalization and in liberalized financial systems.

These results, however, are very sensitive to the sample and the definition of financial liberalization. In the second column we report the results excluding Turkey<sup>7</sup> . The results now are very different. The probability of a crisis is higher only during the 5 years following liberalization and there is no evidence that the probability of a crisis is higher in liberalized financial system.

The evidence is even stronger once we use date of financial liberalization based on Williamson and Mahar (1998) and Drees and Pazarbasioglu (1998) surveys (see table 1). Column 3 reports the results (including Turkey) using the adjusted dates of financial liberalization. The coefficients of the financial liberalization dummy variable is insignificant (and negative) while the coefficients of the dummy variable for the 5 years period following a financial liberalization variable is significant and positive. Thus, there is supporting evidence

> 6 The results are simialir when we use other definition such as 3 years period instead of 5 years.

> 7 One reason to exclude Turkey is that Turkey had additional banking crises during 1980-95, but these crises were not included in their panel because of missing data.

17
outcome indicators include the number of years of schooling the child completed by the time of the survey. Limited information on school performance does not allow us to assess the quality of education. As far as health is concerned, VLSS surveys include anthropometric information. From data on height and weight, we compute the body mass index (BMI) for each child. The BMI of an individual is the ratio between her weight (in kg) and the square of her height (in m). We then compute the z-scores for these anthropometric measures using the UK reference growth charts. The computation follows Cole (1990). The measures hence obtained are arguably comparable across gender and age groups; even though the reference group consists of British individuals, they apply to other countries as well (see Wagstaff et al., 2003 for an application to Vietnam). As expected, Vietnamese children are well below the UK average. They are more than two standard deviations below the UK reference average height and weight (see Table 3, panel A). The average BMI of our sample is also more than one standard deviation below UK reference group average. Although the construction of such scale was aimed at addressing the issue of childhood obesity in the UK (see Cole et al., 2000), these measures are also informative about the extent to which Vietnamese children are undernourished or malnourished (Wagstaff et al., 2003). Thus, in our sample, an increase in any of the aforementioned anthropometric measures will consistently indicate better health status on average. Table 3 shows the average weight, height, BMI and years of schooling for our sample population. Children in our sample are 12 years old on average, and are 1.3 m tall, weighing 29 kg, with an average of 5 years in school.

We then estimate the following equation: in which Yij is the outcome of interest (education and health) for child i born in year tij into family j, and Xij includes individual controls: i’s gender and i’s birth order. Our main speci fi cation consists of considering G<sup>or</sup> ij<sup>,thedummyvariablewhichisequalto1ifchildiisborninayearauspiciousfor</sup> either boys or girls, and 0 otherwise.<sup>7</sup> Table 4 panel A shows the result from the estimation of (2) . We observe a statistically signi fi cant difference in human development between children born in auspicious years and those not. Whether we look at years of education or BMI-for-age, boys and girls born in these years considered to be auspicious for either boys or girls, perform better on average. The result on schooling (columns (2),

> 7 Unless speci fi ed otherwise, auspicious years will henceforth refer to these years for which Gorit<sup>= 1.</sup>

10
**Table 2: Descriptive Statistics and Treatment Balance**

||Control<br>Infor|Information<br>mation Experi|p-value<br>ment|Info only|Ratings only|Negative Comments<br>Ratings Experiment|All Comments|P-value|
|---|---|---|---|---|---|---|---|---|
|_Owner Characteristics_|||||||||
|Female|0.23|0.26|0.582|0.28|0.27|0.20|0.28|0.153|
|Age|38.0|39.2|0.224|38.7|39.1|39.2|39.7|0.732|
|At least 2 years college|0.62|0.65|0.446|0.65|0.66|0.62|0.65|0.885|
|_Firm Characteristics_|||||||||
|Construction sector|0.20|0.18|0.426|0.17|0.19|0.20|0.17|0.796|
|Entertainment sector|0.09|0.10|0.675|0.12|0.13|0.08|0.09|0.213|
|Hospitality sector|0.19|0.20|0.652|0.19|0.20|0.23|0.19|0.832|
|ICT sector|0.14|0.13|0.454|0.13|0.16|0.11|0.12|0.579|
|Light Manufacturing sector|0.38|0.39|0.812|0.40|0.32|0.38|0.45|0.070|
|Age of firm|9.5|10.7|0.157|10.0|9.8|11.4|11.4|0.073|
|Monthly sales (USD)|2541|2194|0.511|2007|2626|2037|2101|0.751|
|Number of Employees|5.9|5.9|0.527|6.3|5.9|5.8|5.8|0.505|
|_Use of Service Providers_|||||||||
|Used an HR Firm|0.05|0.04|0.935|0.05|0.06|0.03|0.04|0.678|
|Uses Accounting Firm|0.02|0.03|0.376|0.05|0.03|0.03|0.02|0.377|
|Uses Marketing Firm|0.02|0.03|0.564|0.04|0.04|0.01|0.03|0.095|
|_Reasons why SMEs don't use_|||||||||
|Don't know any providers|0.30|0.26|0.564|0.25|0.25|0.28|0.27|0.896|
|Find it difficult to judge quality|0.38|0.37|0.785|0.35|0.39|0.35|0.38|0.828|
|Lack of supply of good quality|0.24|0.23|0.700|0.22|0.27|0.19|0.23|0.445|
|Difficult to trust providers|0.39|0.41|0.268|0.36|0.40|0.44|0.44|0.369|
|Too much hassle to find providers|0.38|0.36|0.419|0.30|0.44|0.34|0.37|0.044|
|Think the returns are low|0.33|0.35|0.128|0.34|0.39|0.36|0.33|0.523|
|Lack funding to pay for services|0.51|0.57|0.047|0.57|0.56|0.57|0.58|0.976|
|Are confident they could find HR|0.32|0.37|0.152|0.45|0.36|0.30|0.35|0.020|
|Are confident they could find marketing/accounting|0.28|0.33|0.089|0.39|0.34|0.25|0.33|0.045|
|Sample Size|297|757||187|187|183|200||

Notes: information experiment assigns firms to a control, or to a treatment group which gets provided information on the business marketplace. The information treatment is further subdivided into four types of information provided, for a ratings experiment. P-values test for equality in means, after adjusting for randomizing on city (Lagos vs Abuja).

21
emerging as credible channels of collective action as envisaged, and in many cases suffer from low participation rates and elite capture as noted in reviews of empirical studies (Barrera-Osorio et al., 2009; Bruns et al., 2011).

Government-sponsored reforms to induce community participation in schools have faced similar challenges in Pakistan. The context for this study is Sindh – the second largest province of Pakistan, which has a dense network of public schools that frequently lack basic facilities. More than half of these are one-teacher schools which are prone to temporary closures. A combination of resource shortages, poverty and weak state capacity results in sub-optimal provision of education, leaving a large majority of rural children out of school (Pakistan Social and Living Standards Measurement (PSLM) survey, 2010-11). Dominance of feudal landlords and high levels of ethnic and caste fragmentation in Sindh frustrate any meaningful attempt to invigorate participation of communities to improve service delivery (Miguel and Gugerty, 2005; Hussain et al., 2013).

School grants were introduced in 2001 to transfer authority to elected SMCs, promoting communities’ interest in managing schools, making teachers accountable, and encouraging parents to enroll and retain children in schools. However, these funds remained largely underutilized, and in certain cases were misappropriated. Transfer of funds alone was inadequate in achieving the intended engagement of communities in the school improvement process. A potential explanation is the lack of a mechanism to induce inclusive, broad-based participation of communities with SMCs and schools. In the absence of such mechanisms, Bardhan and Mookherjee (2000) note, decentralized structures are prone to elite capture.

4
The estimations show a different picture for the general work experience, measured by age and its quadratic term. The small magnitude of the coefficients indicates that, work experience acquired prior to migration matters less or not at all for the occupational placement in the US. In addition, the prevalently quadratic shape of the relationship between occupational placement and age (exceptions being the first and the last period of evaluation for the 1975 arrivals) suggests that migrating at an older age is associated with a lower occupational placement. In most cases, the highest occupational placement is attained when the migrant is in his thirties.

The coefficients of the education dummies suggest that, as expected, the higher the educational level, the higher is the occupational placement index. In particular, having a bachelor’s or a higher degree is associated with an increase in the occupational placement by 7080% compared the “no schooling” scenario. The magnitudes of the coefficients for all explanatory variables depend on the choice for the dependent variable (as evident when comparing Table 4 with Annex Table A1), however the sign and the factors’ order of importance stay the same.

We illustrate country-of-origin effects graphically using the occupational placement of our hypothetical individuals where the predictions are based on the estimated coefficients of equation 1. Figure 1 presents the 1990 ÔP by country for the hypothetical individual arriving in the US in 1985. The results suggest that entry level occupational placement of skilled male US immigrants varies greatly by country of origin. The highest level of performance is attained by migrants from developed countries (such as Australia and Canada with scores of 85 and 79 respectively) while the lowest indices are seen among those from Latin American countries (such as Mexico at 47).<sup>20</sup> These patterns confirm findings in Mattoo et al. (2008).

The progress within the ten years closest to migration is presented in Figure 2 where we plot the change in OP (i.e. ΔÔP) between years 1990 and 2000 in the y-axis and the original ÔP in 1990 in the x-axis for the 1985 arrivals. The same exercise is performed for the 1975 arrivals in Figure 3a. The negative correlation between the _entry level_ OP and _change_ in the OP over the next decade in Figures 2 and 3a show that there is significant improvement in the occupational placement levels for skilled immigrants coming from different countries. Additionally, this negative correlation suggests the existence of a convergence effect such that the differences in

> 20 For comparison, as of Census 1990, the weighted average occupational index calculated for all US-born skilled males (irrespective of wage or employment status) is about 77.

12
Policy Research Working Paper 6711

# **Abstract**

Two otherwise identical firms that enter the same market in different months, one in January and one in December, will report dramatically different annual sales for the first calendar year of operations. This partial year effect in annual data leads to downward biased observations of the level of activity upon entry and upward biased growth rates between the year of entry and the following year. This paper examines the implications of partial year effects using Peruvian export data. The partial year bias is very large: the average level of first-year exports of new exporters is understated by 65 percent and the average growth rate between the first and second year of exporting is overstated by 112 percentage points. This paper re-examines a number of stylized facts about firm size and growth that have motivated rapidly expanding theoretical and empirical literatures on firm export dynamics. Correcting the partial year effect eliminates unusually high growth rates in the first year of exporting, raises initial export levels, and shifts 10 percent of market entrants from below to above the median size. Revisiting an older set of facts on firm size and growth, the paper finds that correcting for partial year biases reduces the number of small firms in the firm size distribution and weakens the negative relationship between firm growth and firm size.

This paper is a product of the International Trade Unit, Poverty Reduction and Economic Management Network. 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://econ.worldbank.org. The authors may be contacted at jreyes2@worldbank.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
Policy Research Working Paper 9521

# **Abstract**

Can repatriation inflows impact firm behavior in origin countries? This paper examines this question in the context of repatriation inflows from the United States and Mexico to El Salvador. The paper combines a rich longitudinal data set covering all formal firms in El Salvador with individual-level data on all registered repatriations from 2010 to 2017. The empirical strategy combines variation in the municipality of birth of individuals repatriated over 1995–2002—before a significant change in deportation policies—with annual variation in aggregate inflows of repatriations to El Salvador. The findings show that repatriations have large negative effects on the average wages of formal workers. This is mainly driven by formal firms in sectors that face more intense competition from the informal sector, which deportees are more likely to join. Repatriation inflows also reduce total employment among formal firms in those sectors. Given that most deportees spend less than a month abroad, these findings suggest that the experience of being detained and deported can have strong negative effects not only on the deportees, but also on their receiving communities.

This paper is a product of the Poverty and Equity Global Practice and the Development Research Group, Development Economics. 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 ldinartediaz@worldbank.org and hwinkler@worldbank.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
global export growth. Contrasting with ECA exports to the world, for the small economies of the ECA region, most of the export growth to EAP was explained by growth at the extensive margin, and in particular, by selling more of the same products to new markets. Like with ECA exports to the world, the larger economies in the ECA region (i) have more of their export growth toward EAP explained by increases in the intensive margin, that is, exporting more of the same products to the same destinations, and (ii) have lower extinction rates of trade flows. One of the key challenges for the small economies of the region to deepen their diversification and export growth paths is to tackle the constraints to export flow survival. Further research would be needed to identify what are the binding constraints faced by export flows to remain active.

# **References**

Haddad, M., Lim, J., Munro, L., Saborowski, C., & Shepherd, B. (2011). Volatility, Export Diversification and Policy. In M. Haddad, B. Shepherd, M. Haddad, & B. Shepherd (Eds.), _Managing Openness_ (pp. 135-144). Washington, DC: World Bank.

Hummels, D., & Klenow, P. (2005, February). the Variety and Quality of a Nation's Exports. _American Economic Review, 95_ (3), 199-218.

Imbs, J., & Wacziarg, R. (2003). Stages of Diversification. _American Economic Review, 93_ (1), 63-86.

- Leamer, E. (1984). _Sources of International Comparative Advantage: Theory and Evidence._ Cambridge, MA: MIT Press.

Lederman, D., & Maloney, W. (2012). _Does What You Export Matter? In Search of Empirical Guidance for Industrial Policies_ . Latin American Development Forum Series, Washington, DC: The World Bank.

Lederman, D., & Maloney, W. (2007). _Natural Resources: Neither curse nor Destiny._ Washington, DC: World Bank and Stanford University Press.

Reis, J., & Farole, T. (2012). _Trade Competitiveness Diagnostic Toolkit._ Washington, DC: World Bank.

22
# **2.2 Literature on welfare impacts of food price changes**

As mentioned before, the impacts of food price changes have received much attention in the aftermath of the 2007-08 global price spike. While a complete review of these studies is beyond the scope of this paper, we focus here on studies that have examined this subject in Mozambique or other countries in Africa that offer a similar context. Overall, the short-term impact of earlier food price spikes in Africa has mostly been found to result in a net increase in poverty in most countries. However, there is a large variation in impacts across countries and within a country – across rural/urban areas, as well as across spatial regions. A second observation stemming from the literature is that relaxing the household supply and demand response assumption appears to have less of an effect on the results relative to the importance of dealing with differences in consumer and producer price rises.

The common approach has been to use CV calculations based on equation (2), with varying degrees of simplifying assumptions. Some studies have used the first-order approximation in Equation (3), identical to Deaton’s approach. For instance, Wodon et al., (2008) use household survey data for twelve West and Central African countries to examine the impact of the 2007-08 price rise. They present estimates of the impact on poverty based on the Deaton methodology under two different scenarios – first, when both consumers and producers face the same price rise, and second, when only consumers face the price hike. The upper-bound (results from the second scenario, considering only consumer price rises) of their poverty impact estimates, with a 50 percent increase in food price of staples, range from 1.8 percentage points in Ghana to 9.6 percentage points in Senegal. Their analysis indicates that the impact is mediated by the share of the food commodities undergoing price changes in the consumption expenditure of households as well as the degree of dietary diversity in food consumption. As expected, they also find significant differences in urban and rural areas, with poverty impacts being higher in urban areas in general. Perhaps surprisingly, in three of the countries in their sample – Ghana, Senegal and Liberia – they find that the impact on poverty is higher in rural areas (Wodon & Zaman, 2008).

Another study utilizing data from multiple developing countries is by Ivanic & Martin (2014) who examine the impact of the 2010-11 food price surge. Their sample includes 28 low and middleincome countries, but the sample is not limited to African countries and considers price changes 8
Step (iii) differs depending on the ownership of the damaged asset. Federal assets are fully covered by Fonden and reconstruction is executed by a federal entity. State or municipal government assets only have partial Fonden coverage (50% in most cases), and reconstruction is executed by both federal entities and private service providers. The partial Fonden coverage has been successful at enticing local governments to participate in the Fonden process. Nonetheless, the greater degree of coordination with local governments implies that federal owned assets are likely to be reconstructed in shorter time frames. Average projected reconstruction time is seven months.

Step (iv) involves the publishing of detailed records on post-disaster allocations. This real time publication occurs via the website of the Mexican Secretariat of the Interior. Readers interested in further details are referred to Chapter 3 in World Bank (2012).

Following this disbursement process, in a year of frequent and severe natural disasters like 2010, the program responded to 54 disasters, with some of those disasters affecting areas that spanned over 94 municipalities. During that year alone Fonden provided $6.4 billion (PPP, constant 2005 international dollars) in rapid reconstruction funds. In an average year Fonden responds to 33 disasters, and on average 14 municipalities are affected per disaster. Average municipal Fonden expenditures amount to roughly $4.2 million and median expenditures to $1 million. Overall median yearly program expenditures amount to $972 million, or $8.3 per capita.

# **Mechanisms to mitigate the impact of disasters**

As previously mentioned, the bulk of Fonden expenditures is related to reconstruction efforts. These efforts include the reconstruction of federal and state roads, the provision of funds to reconstruct low-income housing, and the rebuilding of hydraulic, health, and educational infrastructure. These expenditures can provide a double gain to economic development. First, by coping with the losses created by natural disasters. Second, by enabling local governments and households to reallocate resources from safer but inefficient low-risk low-return productive activities to more risky higher-yielding activities.

Our current analysis estimates the impact of Fonden on economic activity at different points in the post-disaster period. The focus of our analysis takes place in the 2004-2013 period when road expenditures accounted for the bulk of overall expenditures.<sup>2</sup> Accordingly, we expect Fonden to affect economic activity primarily by enabling municipalities to quickly rebuild their road network following a disaster.

> 2The shares of expenditure by category vary year by year depending on the type of damages that have occurred. During the period of analysis, road expenditures accounted for 57% of overall expenditures, and for more than 65% of expenditures in five of the years analyzed.

4