rafmacalaba/datause-encoder-data huggingface dataset:
It should be clear that program evaluation of EPAs on economic welfare grounds is difficult if not impossible. Thus often –if not always– evaluations of EPAs stop short of an assessment based on welfare grounds, and focus on the more modest objective of assessing whether exports have increased or whether new markets have been opened. This paper is no exception. Our goal is twofold: first to determine whether EPAs are having an impact on exports; and second, to identify the activities and institutional structures of agencies that seem to have positive effects on exports.

In order to answer these questions we undertook a world survey of national EPAs to gather information on their objectives, activities and institutional structure. To answer the questions of what works and what does not work, we then try to econometrically identify the impact on exports of different institutional structures, objectives and activities.

The resulting evidence suggests that on average EPAs have a positive and statistically significant impact on national exports. There is heterogeneity across levels of development, as the efficiency of EPA monotonically increases with GDP per capita. There is also heterogeneity across regions: larger impacts are found in Eastern Europe and Asia, Latin America, and SubSaharan Africa, with agencies in the Middle East and North Africa lagging behind.

There is also evidence that there are important decreasing returns to scale in resources devoted to export promotion, and even negative marginal returns for budgets above a certain level (estimated at $ 1 per capita). Thus, as far as EPAs are concerned, small is beautiful.

In terms of what type of institutional arrangements, objectives and activities lead to a stronger impact on exports our results suggest the following. EPAs should have a large share of the executive board in the hands of the private sector, but a large share of their budget should be publicly funded. The proliferation of small agencies within a country leads to an overall less effective program. EPAs are more effective when focusing on non-traditional exports, or have some broad sector focus (e.g., agriculture, manufacturing, tourism, high-tech, etc...). They should also focus their activities on large firms (which can take advantage of EPAs services), but which are not yet exporters. The use of office representation abroad for multilateral interventions.

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# **2. BACKGROUND AND DATA**

# **2.1 Background**

Since the inception, in March 2011, of the continuing war in Syria 4.6 million registered refugees have fled Syria, primarily to Turkey (2.5 million), Lebanon (1.1 million), Jordan (635,000), Iraq (245,000), and Egypt (118,000), and increasingly to Western Europe.<sup>11</sup> In 2011 there was only a very small outflow of refugees from Syria, reaching 8,000 in Turkey in December 2011. The number of refugees to Turkey then started to grow rapidly in 2012 and continues to do so. Starting in 2014 the Turkish government issued new identity cards to Syrian refugees designed to give more straightforward access to a wider range of basic services outside of the camps; these services include aid, job offers, education, and health care.<sup>12</sup> The registration drive accompanying the new identity cards also dramatically improved the counting of refugees outside camps, providing a far more accurate picture of the number and distribution of Syrian refugees across Turkey. In late 2014, the final year of the analysis in this paper, there were 1.6 million Syrian refugees in Turkey, 86 percent of which lived outside camps (Erdogan, 2014).

Figure 1 depicts the ratio of Syrian refugees to total population for the 26 NUTS 2 subregions in Turkey (the map depicts the provinces which constitute these NUTS 2). The highest ratios are found in Gaziantep (13 percent), Hatay (9 percent), Mardin (7 percent) and Sanliurfa (5 percent) all of which are located on the Turkish-Syrian border, and host 62 percent of all Syrian refugees in Turkey.<sup>13</sup> Areas further away from the border are less affected, with Adana, Istanbul and Konya at a refugee-population ratio of around 2 percent, the next set of subregions most strongly impacted; and all other subregions with a ratio of under 1 percent.

Turkey has had a generous open-door policy toward Syrian refugees, but until late 2014 the refugees had been labeled “guests” under a hazily defined temporary protection measure. Importantly for this paper, for the period studied the overwhelming number of Syrian refugees if employed will have been so informally. In principle, Syrians who entered the country through the official border crossings and who have passports can apply for residence

> 11 UNHCR data from January 2016 available at http://data.unhcr.org/syrianrefugees/regional.php. Refugees were registered by the UNHCR in Egypt, Iraq, Jordan and Lebanon, and by the Government of Turkey.

> 12 New York Times (December 29, 2014) http://www.nytimes.com/2014/12/30/world/europe/turkeystrengthens-rights-of-syrian-refugees.html?_r=0, and Hurriyet Daily News (January 12, 2015) http://www.hurriyetdailynews.com/turkey-provides-15-million-id-cards-for-syrian-refugees.aspx?pageID=238&nID=76788&NewsCatID=341.

> 13 Istanbul has the largest number of refugees (21 percent).

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200,000 facilities in all regions of the United States. IPPS spans approximately 1,500 product categories, all operating technologies, and hundreds of pollutants. It can separately project air, water, and solid waste emissions, and incorporates a range of risk tactors for human toxic and ecotoxic effects. It can also project emissions of some greenhouse gases and several compounds which are hazardous to the ozone layer. Since it has been developed from a database of unprecedented size and depth, it is undoubtedly the most comprehensive system of its kind in the world.

How applicable are US-based estimates to other economies? It is clear that many country-specific factors will affect the accuracy of prototype IPPS projections outside the US. For particular sectors such as wood pulping, average pollution intensity is likely to be higher in developing countries. However, the pattern of sectoral intensity rankings may be similar. For example, wood pulping will be more water pollutionintensive than apparel manufacture in every country. The present version of IPPS can therefore be useful as a guide to probable pollution problems, even if exact estimates are not possible.

Our present goal is to expand the applicability of IPPs by incorporating data from developing countries. The project is therefore moving into the stage of outreach and information sharing with developing countries. Over time, new evidence will be used to develop systematic adjustments for economies with different characteristics.

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WPS4034

# **When instability increases the effectiveness of aid projects**

Patrick Guillaumont<sup>1</sup> and Rachid Laajaj<sup>2</sup>

### **Abstract**

This paper assesses the effect of economic instability on the success of the projects funded by the World Bank, using the outcome of the projects, which is a notation of their overall success determined by the Independent Evaluation Group. It has been argued in macro economic studies that aid effectiveness is higher in vulnerable countries, because it dampens the negative effects of shocks. We show that this finding is not inconsistent with the observation that the success of the projects is lower in an unstable environment. Indeed instability, in particular the instability of exports, harms aid projects as it harms the rest of the economy, while the success of projects decreases when the total amount of aid received increases, due to absorptive capacity limitations. However this decrease is slower when instability is higher, showing a positive effect of aid through its stabilizing impact. We find the same results keeping only the projects funded by non concessionary loans, which suggests that the cushioning effect of aid extends not only to aid funded projects but to whole sets of projects. Corroborating macro economic findings, our results lead to the same conclusion that more aid should be allocated to more vulnerable countries, in spite of the lower success of the projects in an unstable environment: project evaluations cannot include the macro-stabilizing effect of the aid delivered through projects.

## World Bank Policy Research Working Paper 4034, October 2006

_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._

> 1 CERDI Université d’Auvergne and CNRS.

> 2 CERDI and the World Bank Independent Evaluation Group, ( <u>rlaajaj@worldbank.org)</u> .

> We would like to thank Ajay Chhibber for his helpful comments.

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The annual economic opportunity cost of subsistence farming is obtained by taking the mean of _E_ [∆ _πji|Ii_ = 0] over subsistence households that are not moving to the market in each year.<sup>26</sup> The estimate of the opportunity cost is 167’800 Malagasy francs, or 43 percent of profits. Dividing the annual opportunity cost by GDP and taking the weighted sum, we have that moving all subsistence farmers into the market would add an annual 0.46 percent to Madagascar’s GDP. Entry costs and the consequent subsistence of farmers can be very large when measured at the level of the individual facing the cost. However, at the aggregate level, the costs do not seem to be very large, echoing the literature on trade reform and adjustment costs (see Matusz and Tarr, 1999).

# **3.3.3 Robustness**

For robustness, Tables 5a-5c provide first-stage ML profit estimates for values of _λ_<sup>_∗_</sup> set at 10, 20 and 30 percent respectively, allowing for some market sales by subsistence farmers. Unsurprisingly, the larger is _λ_<sup>_∗_</sup> , the more different are the regression results. Few changes are observed on the two profit equations, but results seem less robust for the occupational choice equation. Note from Table 6 that, as we raise the value of _λ_<sup>_∗_</sup> _,_ the entry cost associated with subsistence farming declines.

Table 5d provides profit estimates for _λ_<sup>_∗_</sup> = 0 but with a decomposition of price variables into short-term crops and long-term crops, depending on the length of time it takes for them to grow.<sup>27</sup> While long term price index and volatility variables are significant, only the short term volatility variable is significant. All other coefficients appear to be in line with those reported in Table 4.

A last robustness check is provided in Table 5e. In order to test for production aggregation problems, the switching regression model is estimated on a subsample composed of households producing mainly rice,<sup>28</sup> Madagascar’s most common crop. With 84% of Malagasy

> 26That way, we estimate accurately the opportunity cost, since we only take into account farmers that are really facing the cost.

> 27For the classification of the crops, see table 3.

> 28Since in most of the case, households have two important crops (e.g, she mainly produces vanilla for exports, but also a large amount of rice for self consumption), we considered both of them as main crops.

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2

# **1. Introduction**

World oil prices began to rise significantly in 2004, and reached all-time historic highs in mid-2008. After falling sharply in the latter half of 2008, prices gradually rose to the first half of 2011 and have been fluctuating around the mid-2011 level since. In early 2012, Saudi Aramco contract prices for propane and butane—important benchmark prices for LPG—surpassed their peak in 2008 in nominal and real terms, and nominal gasoline prices in April 2012 also reached the levels seen in mid-2008 (figure 1), followed by a sharp decline. The surges—and wild fluctuations in the case of LPG—in world prices have posed significant challenges to governments in countries where governments control fuel prices and price-setting is highly politicized.

Figure 1: Monthly average world prices of gasoline, diesel, kerosene, and LPG since 2008 <!-- Start of picture text -->
1.40<br>Gasoline<br>1.20<br>Diesel<br>1.00<br>Kerosene<br>0.80<br>LPG<br>0.60<br>0.40<br>0.20<br>0.00<br>Jan 08 Jan 09 Jan 10 Jan 11 Jan 12<br>kilogram<br>Current US$ per liter or<br><!-- End of picture text -->

_Sources:_ Platts Oilgram Price Report and Reuters, various issues. _Notes_ : Free-on-board cargo prices in Northwest Europe of regular gasoline with 92 research octane number, diesel with 0.1 percent sulfur, and jet kerosene; and the average of Saudi Aramco’s monthly contract prices of propane and butane.

For consumers in many countries, the adverse impacts of steep rises in world oil prices on the world market since the end of 2003 have been exacerbated by currency depreciation against the U.S. dollar, in which world oil prices are denominated. Between 2003—before oil prices began to rise—and 2011, currency depreciated in two-fifths of developing countries, broadly evenly split across income categories. In nearly one-fifth of them, depreciation exceeded 20 percent.<sup>2</sup> In contrast, appreciation exceeding 40 percent was disproportionately concentrated in upper-middle-income countries (figure 2).

> 2 It is worth pointing out, however, that depreciation against the U.S. dollar in the preceding eight years was much more serious: more than four-fifths of countries experienced depreciation, and depreciation exceeded 70 percent in one-fifth of them.
finding is in line with Velenchik (1996a, 1996b)."6 Not only do larger firms pay more than smaller firms do in Zimbabwe but they are also more productive as revealed by<sup>the</sup> production function estimates. The impact of the firm size on wages and productivity is both statistically significant and positive but the impact on the latter is far larger than on the former (F = 1022.6, Prob > F = 0.00). A 10-percentage-point increase in firm<sup>size</sup> increases wages by 1.86 percentage points.

**Table 12 Firm Size**

||Prod|uctivity|||Wages||||
|---|---|---|---|---|---|---|---|---|
||Coef.|Std. Err.|t|P>jtI|Coef.|Std. Err.|t|P>ItI|
|lempl|1.366|0.036|37.775|0.000|0.186|0.018|10.577|0.000|
|emplexp|-0.003|0.001|-2.672|0.008|-0.001|0.001|-1.986|0.047|
|empleuro|-0.253|0.137|-1.841|0.066|0.152|0.067|2.273|0.023|
|emplasia|-0.179|0.080|-2.224|0.026|-0.059|0.039|-1.503|0.133|
|emplwood|-0.122|0.026|-4.783|0.000|-0.032|0.012|-2.545|0.011|
|emplmeta|0.042|0.016|2.565|0.010|-0.009|0.008|-1.083|0.279|

In the above sections the importance of the firm size was already mentioned. We can summarize the findings as follows. Larger firms engaged in export activities pay lower wages but are a little less productive. Europeans are paid more than employees of African origin in larger firms, but are also less productive than these ethnic groups, ceteris paribus. Employees working in woods and metals in larger firms are paid<sup>less</sup> than in smaller finns, but they are not less productive.

The employees in firms engaged in R&D are not paid statistically significantly more<sup>or</sup> less than workers in firms not participating in these activities. It should be noted<sup>that</sup> manufacturing workers is a privileged group of workers because they have a<sup>stable</sup> income and often receive extra benefits. It is one of the groups with the highest incomes

> **16** That earnings increase with establishment size has been found elsewhere (see Groshen<sup>(1991).</sup>

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**Table 2: Evidence** **<u>of credit constraints in formal, semiformal, and informal sectors</u>**

||**Total**|||**By w**|**ealth qua**<br>|**rtile**|||
|---|---|---|---|---|---|---|---|---|
|||Q1|Q2||Q3||Q4||
|**Formal sector**|||||||||
|Constrained|0.87|0.96|0.93|***|0.88|***|0.74|***|
|Quantity rationed|0.09|0.08|0.10||0.08||0.09||
|Lack of collateral|0.06|0.06|0.07||0.05||0.05||
|Risk rationed|0.07|0.03|0.04||0.06|*|0.14|***|
|Transaction costs rationed|0.69|0.82|0.76|***|0.70|***|0.49|***|
|**Semi-formal sector**|||||||||
|Constrained|0.71|0.82|0.76|***|0.65|***|0.59|**|
|Quantity rationed|0.32|0.38|0.38||0.28|***|0.25|*|
|Lack of collateral|0.10|0.13|0.12||0.08|***|0.06||
|Risk rationed|0.21|0.13|0.23|***|0.22||0.24||
|Transaction costs rationed|0.62|0.71|0.67|*|0.58|***|0.52|**|
|Quantity and risk rationed|0.07|0.03|0.10|***|0.07|*|0.08||
|**Informal sector**|||||||||
|Constrained|0.58|0.74|0.63|***|0.52|***|0.42|***|
|Quantity rationed|0.36|0.52|0.42|***|0.31|***|0.21|***|
|Lack of collateral|0.05|0.09|0.07|*|0.04|**|0.03||
|Risk rationed|0.24|0.22|0.25||0.25||0.23||
|Transaction costs rationed|0.28|0.38|0.31|***|0.24|***|0.18|***|
|Quantityand risk rationed|0.09|0.11|0.11||0.09||0.06|**|
|**Total Observations**|3294|823|824||823||824||

**Source:** Own computation from WB survey 2011. **Note:** The wealth quartiles are calculated using a principal component analysis based on housing conditions, assets, livestock and land ownership. T-test is performed using as a reference the immediate lower quartile: * significant at 10%; ** significant at 5%; *** significant at 1%

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capital regulations and official supervisory agencies over this period (following Basel guidelines), the reforms are not likely to improve bank stability or efficiency.

The rest of the paper is organized as follows. Section II introduces the 2011-12 BRSS, describing how it has been designed and implemented. Section III examines differences between the regulatory and supervisory framework of crisis and non-crisis countries. Section IV examines recent changes in regulation and supervision distinguishing between crisis and non-crisis countries. Section V concludes. Appendix I presents more detailed survey results, going through every section of the survey, providing an update on the state of regulation and supervision around the world across advanced economies and emerging and developing countries.

# **II.   THE DESIGN AND IMPLEMENTATION OF THE 2011-12 BRSS**

The survey provides data for 143 countries<sup>3</sup> , of which 37 are advanced economies and 106 are emerging markets and developing economies (EMDEs).<sup>4</sup> These include most major economies (all G-20 countries except for Japan and Saudi Arabia) and countries from all regions (Figure 1). Overall, the survey sample provides a broadly balanced representation of countries in terms of level of income and population size.

In terms of topical coverage, the survey is quite comprehensive, providing a unique and valuable set of information on a wide range of issues related to bank regulation and supervision. It contains over 270 questions, some with sub-questions. In total, the survey covers about 630 features of bank regulation and supervision, in the following 14 broad areas: (1) entry into banking, (2) ownership, (3) capital, (4) activities, (5) external auditing requirements, (6) bank

> 3 The 2011–12 Bank Regulation and Supervision Survey is available at http://go.worldbank.org/WFIEF81AP0. Data from previous iterations of the survey are available at http://go.worldbank.org/SNUSW978P0.

> 4 See Table 1 for a detailed list of countries in this survey. The distinction between “advanced economies” and “emerging market/developing/economies” follows IMF’s September 2011 _World Economic Outlook_ .

4
result, employment level is still relatively high. In a way, this labor market state is a transient one. It can evolve into a depressed labor market, as it has happened in Poland in early 2000s, or into vibrant labor market as it has happened in Lithuania at around the same time.

_Limited job opportunities: discouragement._ Hungary is an example of a country where in the face of limited job opportunities a large fraction of jobless workers withdraws from the labor force. Unemployment is thus low, but so is the labor force participation rate (which may be possible thanks to the availability of non-employment benefits). As a result, low unemployment coincides with relatively low employment. The employment effect is similar to that in countries where both the labor force participation and unemployment are higher (the previous group).

_Scarcity of jobs: unemployment and discouragement._ This combination of high unemployment and low labor force participation rates, prevailing in countries such as Bulgaria and Croatia, signifies a depressed labor market, with the resulting low employment level. High unemployment in this case is likely to reflect the fact that many jobless workers (e.g. primary earners, the poor) cannot afford to be out of the labor force and are compelled to actively search for work.

To sum up, labor force adjustment has taken various forms during economic transition. In some countries, changes in labor demand led mainly to changes in unemployment, in others mainly to changes in labor force participation. Moreover, labor market adjustment during the transition has been a dynamic process, with changes in labor market conditions inducing movements between unemployment and economic inactivity (Boeri, 1995).

# **Disproportionately low male employment rates**

The male employment rate is significantly higher than the female employment rate in all transition economies.<sup>2</sup> This is due to the difference in the labor force participation rate, which is much lower for women, rather than the unemployment rate which tends to be similar for men and women (Figure 3).

**Figure 3 Labor force indicators by gender, 2002**

<!-- Start of picture text --> A. Employment/populaion Ratio, 2002<br>80<br>70<br>60<br>Men<br>50<br>Women<br>40<br>30<br>20<br>10<br>0<br>CEE EU15<br>percent<br><!-- End of picture text -->

> 2   This statement is based on data for CEE countries and Russia.  However, it is highly unlikely that the common pattern of higher male than female employment rate does not apply to other ECA countries.

9