rafmacalaba/datause-encoder-data huggingface dataset:
regions of a country. We use a cross-section of more than 40,000 manufacturing and services firms in 79 developing countries. We hypothesize that traditional firm-level characteristics matter less for firms located in core regions, since a firm’s business environment will explain a larger share of a firm’s export behavior.

This paper is structured as followed. In the next section, we compare firms located in the core with firms located in non-core regions to detect significant differences in export performance. We also analyze other performance indicators related to a firm’s business and business environment. In section three, we perform an econometric exercise where we first study the impact of firm-level and regional determinants as well as agglomeration economies on exporting. We also examine the role of location, assessing whether the determinants of exporting are different if firms are located in core versus non-core regions. Based on the results of the empirical analysis, we derive some policy conclusions in section four.

# **2 Descriptive Analysis: Core versus Non-core Regions**

## **2.1 Data**

The World Bank Enterprise Analysis Unit recently published the Enterprise Surveys Indicator Database.<sup>4</sup> This publication is based on enterprise surveys for over 100 countries, over the period 2002 to 2010. Enterprise surveys represent a comprehensive source of firm-level data in emerging markets and developing economies. One major advantage of the enterprise surveys is that the survey questions are the same across all countries. Moreover, the Enterprise Surveys represent a stratified random sample of firms using three levels of stratification: sector, firm size, and region.

The Enterprise Surveys Indicator Database covers a wide range of indicators on firm characteristics and indicators of business environment, innovation and technology, workforce and skills, permits and licenses, infrastructure, finance, and corruption among others. In making use of this dataset, we apply the following rules: (i) We included only the most recent Enterprise Surveys for each country into the analysis. (ii) We dropped high-income countries to cover only emerging or

> 4 See <u>http://enterprisesurveys.org/Methodology/Indicator-Descriptions.aspx</u> for a description of the indicators.

7
19 bias depends on the correlation of the error structures, **em** and ef, in the participation equations of (1) and (2). If em and ef are correlated which is likely the case, a joint estimation of the male-female wage gap equation (14) or (15) along with participation equations (1) and (2) must account for this correlation to yield efficient estimates.

# 3. Data Characteristics

The data used for this paper are drawn from the Peruvian Living Standard Survey (PLSS) household data collected jointly by the World Bank and the Peruvian Instituto Nacional de Estadistica (INE). These data provide detailed socioeconomic information on over 5,100 households and 26,000 individuals. The samples were drawn from a self-weighted national probability sample of Peruvian households and represent an approximate 1/100 sample of the population. The sampling frame is based on a 1984 National Health and Nutrition Survey. About 25 percent of the households in the PLSS were located in metropolitan Lima, 28 percent in other urban areas, and 47 percent in rural areas. The data were collected between June 1985 and July 1986 (see Grootaert and Arriagada 1986).

This paper covers workers aged 14 to 60. The wage earner participation equation is estimated using information for all potential workers. The wage equation, however, is estimated only for those men and women who reported wage remuneration and hours worked in the wage sector as their main occupation during the week prior to data collection. Thus selfemployed and unpaid family workers are excluded from this reduced sample. The wage sample consists of 2,255 men from 1,856 households and 898 women from 783 households, drawn from a total of 6,429 men from 4,142 households and 6,94?
|EmergencyDrought RecoveryProject(EDRP)|Christine E. Cornelius|
|---|---|
|EmergencyDrought RecoveryProject(EDRP)|Christine E. Cornelius|
|Thaba Bosiu Rural Development Project(02)||
|HighwayProject(03)<br>||
|HighwayProject(03)||
|Water SupplyProject(01)<br>||
|Lesotho National Development Corporation Project(02)<br>||
|Lesotho National Development Corporation Project(02)||
|Lesotho National Development Corporation Project(02)||
|Urban Development Project(01)||
|Urban Development Project(01)||
|Urban Development Project(01)||
|Education Project(03)||
|Education Project(03)||
|Education Project(03)||
|Education Project(03)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|HighwayProject(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Education(04)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Health and Population Project(01)||
|Highlands Water EngineeringProject||
|Highlands Water EngineeringProject||
|Highlands Water EngineeringProject||
|Highlands Water EngineeringProject||
|Land Use & Conservation PlanningProject|Peter G. Moll|
|Land Use & Conservation PlanningProject|Peter G. Moll|
|Land Use & Conservation PlanningProject|Peter G. Moll|
local communities collectively proposing the sub-projects that they want; for a SF in Jamaica, the authors found that the process was often dominated by local elites.

In practice, it is very unlikely that all the relevant assumptions are testable (including alternative assumptions made by different theories that might yield similar impacts). Nor is it clear that the process determining the impact of a program can always be decomposed into a neat series of testable links within a unique causal chain; there may be more complex forms of interaction and simultaneity that do not lend themselves to this type of analysis. For these reasons, the so-called “theory-based evaluation” approach cannot be considered a serious substitute for assessing impacts on final outcomes by credible (experimental or NX) methods, although it can still be a useful complement to such evaluations, to better understanding measured impacts.

Project monitoring data bases are an important, under-utilized, source of information. Too often the project monitoring data and the information system have negligible evaluative content. This is not inevitably the case. For example, the idea of combining spending maps with poverty maps for rapid assessments of the targeting performance of a decentralized anti-poverty program is a promising illustration of how, at modest cost, standard monitoring data can be made more useful for providing information on how the program is working and in a way that provides sufficiently rapid feedback to a project to allow corrections along the way (Ravallion, 2001).

The _Proempleo_ experiment provides an example of how information external to the evaluation can carry important lessons for scaling up. Recall that _Proempleo_ randomly assigned vouchers for a wage subsidy across (typically poor) people currently in a workfare program and tracked their subsequent success in getting regular work. A randomized control group located the counterfactual. The results did indicate a significant impact of the wage-subsidy voucher on employment. But when cross-checks were made against central administrative data, supplemented by informal interviews with the hiring firms, it was found that there was very low take-up of the wage subsidy by firms (Galasso et al., 2004). The scheme was highly cost effective; the government saved 5% of its workfare wage bill for an outlay on subsidies that represented only 10% of that saving.

However, the supplementary cross-checks against other data revealed that _Proempleo_ did not work the way its design had intended. The bulk of the gain in employment for participants was not through higher demand for their labor induced by the wage subsidy. Rather the impact 54
# EXCHANGE RATE POLICY IN DEVELOPING COUNTRIES

# W. Max Corden

A distinction can be made between two approaches to exchange rate policy in developing countries: the "real targets" and the "nominal anchor" approach. A related distinction is between an approach where the exchange rate follows other policies and private sector price and wage setting and where it leads them. Part I gives an overview of the two approaches and the assumptions they imply. Part II expounds the "real targets" approach and its implications in some detail. This is really the approach that is now orthodox. Part III expounds the "nominal anchor" approach and its implications, and considers to what extent it might explain the low inflation experiences of the many countries where exchange rates have been (more or less) fixed for long periods. Part IV considers the implications of increasing capital mobility for exchange rate policy, and Part V has some conclusi(ns for policy. The paper draws on examples of exchange rate policies and experiences of a group of seventeen developing countries which are being studied as part of a World Bank project on macroeconomic policies and growth over a longer period. All references to developing countries are to these seventeen as a whole or to particular ones among them.<sup>1</sup> 1 The countries include two that are members of the franc zone - Cameroon and Cote d'Ivoire - so that their exchange rates - have been cimpletely fixed, four namely Argentina, Brazil, Chile and Colombia - that were "chronic inflation" countries before 1973, when they had quite high inflation rates and crawling peg or variable exchange rates even when most other countries had fixed rates and low inflation; and finally, eleven
58 "tariffied' rates of over 30 percent for beef, and close to 200 percent for sugar. How are African countries expected to compete with domestic (OECD) producers when the latter receive such high levels of border protection?r It should also be noted that regionalism is a factor here. Under OECD arrangements industrial countries' exports of many of these products receive significant preferences while developing countries face the full (high) tariffied rates. Aside from the direct border controls on agricultural products, other OECD measures have an adverse impact on African and other developing country exporters of agricultural products. Behind the high wall of external European protection huge surpluses of products like sugar, dairy and beef have been generated. To dispose of these surpluses OECD countries have often resorted to (highly) subsidized exports that have a well documented twofold impact. First, these shipments have displaced developing country producers in third country (export) markets. Second, a similar displacement occurs in the domestic markets of developing countries as local producers are unable to compete with the subsidized foreign suppliers. While many African countries have been (rightly) criticized for domestic policies that disadvantage local agricultural producers, more attention should also be given to the potential adverse influence of foreign (OECD) export practices.23

# E. AnDrovriate OECD Policy Action on NTBs

OECD nontariff trade barriers have contributed to Africa's relatively poor trade performance in some specific product sectors, although they do not seem to have played a major role in the general decline. With a few exceptions African countries have not been subject to MFA restrictions, and no African country has faced a .voluntary' export restraint. Similarly, in the 1980s only 2 OECD antidumping actions were taken against any sub'Available evidence suggests that the benefits of agricultural trade liberalization may be very impressive for developing countries such as those in Africa when viewed in terms of domestic employment effects. This conclusion is based on studies by the International Labor Office (Lydall, 1975) which show that developing countries may use (on average) up to 30 times as much labor per unit of agricultural output as some developed countries. Furthermore, the ILO studies conclude that the linkage and multiplier employment creation effects in the agricultural sectors of developing countries are among the largest of all industry groups. The implications of these findings are that increased opportunities for agricultural exports could make a significant contribution to alleviating the basic social and employment problems in African countries.

2It should be noted, however, that these practices may have benefitted developing countries that were net food importers to the extent that they lowered international prices and net food import bill.
<!-- Start of picture text --> 2<br>©oO<br>><br>&<br>LQ<br>©<br>ag<br>ct<br>2o<br>ow<br>.N<br>Cc<br>§a)— N _-—* _~——* —-——-~Ts aL<br><x _— mY<br>~ xk NN<br>c “7 SA<br>D<br>©CcO ee<br>= oO<br>Oo<br>10 20 30 40 50 60 70 80 90<br>Urbanization Rate at the Start of Yeart (%)<br>Urban Natural Increase<br>(Per 100 People) —e—1 ~An 1.5 2 2.5 —#—3<br><!-- End of picture text -->
2 Unfortunately this doesn't seem to happen anymore. Somehow in the midst of the policy debate of the last few years we seem to have lost our control over language and what for some is a "liberalized economy" for others is a "nonliberalized" economy; for some "outward oriented" means a certain thing, while for others it means a different one.

There is little doubt that the policy discussion on trade regimes has become highly<sup>4</sup> deologized. Perhaps the best example of the current confusing state of affairs is that the case of South Korea is now considered an example of the validity of different (almost opposing) views regarding commercial policy. For some (i.e., World Bank 1987) Korea is the best example of an outward oriented liberalized economy, while for others (Collins and Park 1988, Sachs 1987) Korea is a prime example that in order for a small developing economy to grow (very) fast it should avoid an abrupt liberalization. Certainly, either one of these camps is not right in its assessment, or the participants of the debate are giving a different meaning to the same terms.

Recently, we have witnessed a shift in the meaning of "liberalization". In the more traditional policy literature of the 1960s and 1970s trade liberalization was defined in a very general way; what economists usually meant was some relaxation of trade and exchange controls. In fact, in the by now classical NBER study on trade regimes directed by Bhagwati (1978) and Krueger (1978) a liberalization episode was defined as a more extensive use of the price mechanism that would reduce the anti-export bias of the trade regime. In her review article on the problems of liberalization presented at the World Bank conference on the dynamics of liberalization, Krueger (1986) reaffirmed this general definition and argued that even a (real) devaluation in the presence of QRs constituted a liberalization episode.
**Table 8.** Heterogeneous treatment effects - HIV incidence: Risk preferences

|Sample||Panel A: Al|l|Panel B: R|isk-lovers|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|Any lottery×Risk-loving|-0.122<sup>***</sup>|-0.107<sup>**</sup>|-0.100<sup>**</sup>|||
||(0.042)|(0.039)|(0.039)|||
|Risk-loving|0.123<sup>***</sup>|0.111<sup>***</sup>|0.104|||
||(0.033)|(0.032)|(0.031)|||
|Any lottery|-0.003|-0.005|0.223|-0.124<sup>***</sup>|-0.114<sup>***</sup>|
||(0.018)|(0.018)|(0.141)|(0.036)|(0.033)|
|Mean control group|0.139|0.139|0.139|0.211|0.211|
|Baseline controls|No|Yes|Yes|No|Yes|
|Full set of control×treatment covariates|No|No|Yes|-|-|
|Observations|1420|1420|1420|525|525|

Note: Sample of individuals aged 18-32 at baseline who responded to the hypothetical risk aversion question. Panel A: Full sample. Panel B: Risk-loving individuals. See notes to table 4 for the definition HIV incidence. Risk-loving is an indicator variable taking the value 1 for respondents who, at baseline, prefered a fixed amount of money equal or above 250 maloti instead of a lottery with 50% chance of winning 500 maloti, and 0 for respondents who prefered a fixed amount of money below 250 maloti instead of a lottery with 50% chance of winning 500 maloti. Any lottery is high and low lottery combined. The control variables are STI status at baseline and all household characteristics listed in panel B, table 2. All regressions include village fixed effects. Robust standard errors in parentheses, clustered at the village level. *** 1% , ** 5% , * 10% significance.
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17

- --

- (x) What institutional strengthening might be needed to ensure MCW or any other designated ministry -- could discharge the above duties effectively?

It is not easy to conduct such contsultations. The process involves: preparation of an initial consultation document (outlining the scale of the problem being addressed in the consultations, summarizing the options available, setting down what the government is willing to do to improve matters, and then setting out the substantive issues to be discussed during the consultation process), orchestrating the consultations themselves and, based on the results of the consultations, drafting the ensuing White Paper summarizing the government's policy and clearing the way for the changes in laws and legislation -- and reform of the institutions -- needed to implement the new policy. In view of this complexity, it was suggested that the government might request technical assistance to finance a secretariat to help it to undertake the consultations.

# 6. Multi-Year Programming

18. The work in Tanzania stopped short of the extended analysis normally undertaken as part of a fully-fledged public expenditure review. The methodological framework nevertheless lends itself to such an analysis and provides an ideal way of examining the inter-action between sector level strategies/expenditures and the impact these have on the overall macro-economic resource envelope. For example, Table 4, the Road Sector Financing Plan, shows actual revenues and expenditures for 1985/86 and 1986/87, budgeted figures for 1987/88 and a generalized one year Proposed Financing Plan. In a public expenditure review, the latter figure would generally be replaced by a three to five year forward plan, showing the likely consequences -- in more specific temporal terms -- of the recommended changes in proposed expenditure levels and revenue mobilization.

19. The same format could also have been applied to airports and transport enterprises; the latter might have been treated separately. or could have been dealt with by treating separately the large, problematical enterprises (for which specific improvements had been recommended) and combining the
of human capital on the outcome variables survives a number of robustness checks such as dropping the state of Maharashtra from the sample, removing the state and year fixed effects from the specification and adding the _level_ of institutional quality as an explanatory variable.

# **4. Disaggregated results**

In this section we look at the disaggregated sectors within registered manufacturing and services. These sectors are quite diverse and fitting a single regression at the aggregate level does not allow us to exploit the diversity to better understand the effect of human capital on output. For example, we found above that the highly skilled had a strong effect on the services sector but a weak one on the other sectors. The most natural explanation of this is that the service sectors are the most skill intensive sectors and hence likely to benefit more from a greater availability of human capital. Testing for this requires differentiating across sub-sectors by their respective skill intensities which is the main goal of this section.

We pool data for the 5 main services sectors and 16 registered manufacturing sectors at the ASI 2 digit level. These sectors are listed in Table 6. Consistent data on output of these sectors are available for the time period 1980-1997.

Diversity across sectors is captured using factor intensity ratios which reflect the relative importance of the explanatory variables across sectors. These factor intensity ratios are computed using the input-output matrix for India. To appropriately map the sectors in our data onyo the ones in the input-output matrix we had to group our initial set 11
In the first section of the paper some descriptive statistics on regime change are presented to motivate the research questions. In the second section of the paper, a simple model of an “autocracy game” is developed within the context of similar models in the previous literature. The model shows how autocratic elites are able to extend the political franchise to prolong the life of an otherwise unpopular regime. This approach contributes to the literature by differentiating between the costs of the conflict through conflict expenditure and the costs of conflict associated with missed opportunities for cooperation. The sum of both of these costs is referred to as the “civil peace dividend.” Additionally, the model allows for continuous levels of autocracy – from the most repressive, autocratic regimes to those regimes that are nearly democracies – in contrast to previous discrete models in the literature. A brief comparison in the form of a “democracy game” is introduced. The final section presents some brief empirical results which motivate future research questions and concludes.

# **1. Some Descriptive Statistics**

Democracy is on the march. According to the Polity IV data set (Marshall and Jaggers, 2003), the number of democracies in the world has increased from 20 in 1945 to more than 80 in 2003<sup>2</sup> Though many of these new democracies are new states, a similar trend is not seen in autocracies, which saw a rise from approximately 50 in 1945 to more than 100 in the late 1970s and then declined to less than 80 autocracies in 2003. Many of these autocracies became functioning democracies in the last quarter of the 20<sup>th</sup> century during the so-called “Third Wave” of democratization (Huntington, 1991).

Huntington suggests that industrialization and economic development lead to a burgeoning middle class that ultimately demands democratic representation. Though there has been an overall trend in democratization in the world accompanied by economic development, the general trend that constitutes Huntington’s Third Wave does not capture the autocratic fits and democratic starts that many of these countries have experienced during their political journey. How did Botswana transition so smoothly out of British rule and how has Honduras

> 2 The list of countries and regimes included in the study is available as an appendix to the paper.  Autocratic regimes are defined as any regime with a Polity score of less than 3 in its first year.  Statistics for regime start date and the length of survival of a regime were compiled with reference to Krieger (2001) and clarification from CIA (2005) and Geddes (1999), as necessary.  Polity is the democracy score less the autocracy scores from the Polity IV data set.  Both of the component measures range from 0 to 10, therefore polity scores are range from -10 (Absolute autocracy, no democracy) to 10 (Democracy, no autocracy).  For more information, see Marshall and Jaggers (2003).

3