rafmacalaba/data-use-mentions-extended huggingface dataset:
damaging) for economic development if a government enforces them in a mechanistic and rigid manner. Indeed, the incentive structures and modes of government control are changing so fundamentally in contemporary China that the authorities' ability accurately to forecast future skill needs, and to use the results as the basis for reliable planning of VTE must be seriously doubted. In general, the climate of economic reform poses a particular challenge for VTE planning and development, mandating the need for a system able to adapt in fundamental ways to changes in economic management.

9. There are some solid grounds for optimism in this respect. Planning for manpower match and even for some aspects of the financing of the VTE system in China is already quite decentralized, incremental, and based on a good deal of formal and informal consultation and consensus building. In the current circumstances, therefore, China's present mode of "bottom-up' manpower forecasting, with only the most general guidelines from Beijing as to how many and what types of skilled workers to train, is to be welcomed as being likely to contribute to successful economic outcomes. The process, while structurally appropriate, could be improved through better information at all levels. Data on employment outcomes would be especially useful in policy and planning decisions.

10. In addition, the curricula of the SVS have been able to provide skills relevant to the service sector and to self-employment. These schools are scheduled for large increases in enrollment. In combination with evolving linkages with employers and considerable school initiative in finding work for graduates, SVS have the potential for providing large-scale, flexible, and relatively low cost formti of skills training to support the government's goal of expanding service sector and self-employment.

11. The present report has focused on the external efficiency of the VTE system in China. However, the internal efficiency of the system (that is, the effectiveness with which available resources are utilized) suffers from a number of weaknesses:

- (a) training units are often too small;

- (b) curricula
increased in harder-hit regions. This indicates that trade-displaced workers spend some time unemployed or out of the labor force, but eventually nd reemployment in the informal sector. The evidence thus suggests that informal employment constitute an important margin of labor market adjustment in response to trade shocks. In order to shed light on this issue, Dix-Carneiro et al. (2021) build an equilibrium model of a small open economy with labor market frictions and imperfectly enforced regulations. They estimate the model using data from Brazil and use counterfactual simulations to understand how trade aects economic outcomes in the presence of informality. They nd that trade openness leads to large declines in informality in the tradable sector. On the other hand, the eects of trade openness on informality in the non-tradable sector are more context-dependent. As a result, the overall eect of trade on informality is ambiguous, and generally small. They also nd that trade openness is associated with substantive increases in productivity and that the productivity gains from trade are understated in studies focusing exclusively on the formal sector of the economy.

# 5.2 Credit reforms

## 5.2.1 Repossession of collateral

There is a large literature documenting the relationship between collateral and better credit conditions, in particular larger loan volumes and lower interest rates.<sup>27</sup> To remove ineciencies in the auto loan and other credit markets, the Brazilian government enacted in 2004 the Law 10.931, the Lei de Alienação Fiduciária (Fiduciary law), which aected the auto loan, mortgage, and capital markets. Among other changes, the credit reform simplied the sale of repossessed cars used as collateral for auto loans. Before the reform, even though banks were allowed to repossess the autos of borrowers who failed to repay their loans, they could not resell these repossessed cars without court approval. As a result, the time from repossession of a car to its resale by the bank averaged more than two years. After the reform the process
The core module was designed to maximize its consumption share based on NBHS 2009 consumption, and therefore contains all the most commonly consumed items. This includes staple foods such as dura, maize, onions, okra, common types of flour (e.g. millet, maize, cassava, and groundnut flour), common types of meat (e.g. goat, sheep, poultry, beef), and some fruits. The nonfood core module similarly captures common expenditures including fees for education, common types of transportation, common medicines and health related expenditures, and clothing. Optional modules were constructed using an algorithm to assign items iteratively to optional modules so that items are orthogonal within modules and correlated between modules.<sup>23</sup> This step is followed by the actual data collection. Conceptual division into core and optional items is not reflected in the layout of the questionnaire. Rather, all items per household are grouped into categories of consumption items (like cereals, meats, etc.). Using CAPI, it is straight‐forward to hide the modular structure from the enumerator. For ��� ��<sup>∗</sup> � each household, only the core module y� and one additional optional module y� are collected. In each enumeration area, 12 households were interviewed with an ideal partition of three households per optional module.<sup>24</sup> The assignment of optional modules was stratified per EA to ensure that an equal number of households are assigned to each optional module. This served to minimize potential EA effects during the imputation process. Household consumption was then estimated using the core module, the assigned module and estimates for the remaining optional modules: where K<sup>∗</sup> ∶��1, ... , k<sup>∗</sup> �1, k<sup>∗</sup> �1, ... , M� denotes the set of non
and the terms would be somewhat different if the reference year was t+n, rather than t. Because of this path-dependence, there is a residual term when the decomposition is calculated for a single reference year t, denoted _Rt_ .<sup>31</sup>

> 28 Bourguignon, Ferreira and Lustig (2005) discuss the advantages of a disaggregated counterfactual analysis of distributional dynamics, and propose a general methodological framework. 29 See Ferreira and Paes de Barros (1999).

> 30 Datt and Ravallion (1992) rely on grouped data, and must therefore use parameterized estimates of the Lorenz curve in order to simulate the counterfactual distributions. Because we use household level data, we compute the counterfactual poverty terms P(z/μx , Ly), x≠y, by rescaling the distribution in year y with the ratio μx/μy.

> 31 As Datt and Ravallion suggest, this residual term can be interpreted as capturing the interaction between growth
**Figure 3.4**

**Gini coefficient of household per capita income, skilled-unskilled and highschool-dropouts wage premiums. 16 LA countries, 1989-2009**

<!-- Start of picture text --> .6 .8 1 1.2 1.4 1.6 .2 .4 .6 .8 1<br>Wage Premium, Skilled-Unskilled Wage Premium, Highschool-Dropouts<br>.65 .65<br>.6 .6<br>.55 .55<br>.5 .5<br>Gini Coefficient HPCI Gini Coefficient HPCI<br>.45 .45<br>.4 .4<br><!-- End of picture text --> Source: own computations based on SEDLAC (CEDLAS and World Bank).

27
26

# **Table 1:  Summary Data on Non-Remittance and Remittance-Receiving Households, Ghana, 1988/99 (cont’d)**

|Variable|Receive no<br>remittances|Receive internal<br>remittances<br>(from Ghana)|Receive<br>international<br>remittances<br>(from African<br>or other<br>countries)|t-test (Internal<br>remittances vs.<br>no remittances)|t-test<br>(International<br>remittances vs.<br>no remittances)|
|---|---|---|---|---|---|
|**Networks**<br>Head of household is of Asante<br>ethnicity (1 =yes)|0.15<br>(0.36)|0.21<br>(0.41)|0.29<br>(0.45)|3.91**|7.59**|
|**Income**<br>Mean annual per capita income<br>(excluding remittances) in Ghanaian<br>cedis|687,912<br>(1,104,368)|530,201<br>(821,350)|724,078<br>(1,245,911)|-6.28**|0.06|
|N|3,517|2,139|488|||

Notes: N = 5,998 households; 146 households receive both internal and international remittances. All values are weighted; standard deviations in parentheses. In 1999, US$ 1.00 = 2,394 Ghanaian cedis.

Source: 1998/99 Ghana Living Standards Survey (GLSS 4).

- Significant at the 0.05 level.

- ** Significant at the 0.01 level.
-|-|-|13.41|
|EMP|5.17|6.27|-|-|EMP|0.35|12.31|0.77|1.53|
|||Females|||||Females|||
|From\To|NP|UE|PT|FT|From\To|NP|UE|PT|FT|
|NP|81.31|-|-|-|NP|85.11|-|-|-|
|UE|-|9.17|1.45|3.29|UE|-|1.68|1.26|2.69|
|PT|-|-|1.03|-|PT|-|-|1.51|-|
|FT|-|-|-|1.13|FT|-|-|-|3.72|
|EMP|1.63|0.99|-|-|EMP|-|3.36|0.16|0.51|

Notes: Author’s calculations based on 2017 UNDP-WB-EC Roma Regional survey. Abbreviations: FT= employed full-time; PT= employed part-time; U= unemployed; NP= non-participant; EMP= Past Employment. Each matrix sum up to 100. Transitions are found from selfreported transitions. Past job schedule is not available in the survey, for this reason past jobs can only be characterized as EMP.

**From the self-reported changes in the labor market, we build male and female transitions.** All the matrices in the middle and bottom panel of table 6 sum up to 100. In the survey, only the time from the last job for the nonworkers and job tenure for the workers were collected. Consequently, only changes from previous employment to the nonwork states can be identified. Moreover, as we assumed that the current worker moved from unemployment, we
Next, we argue that while exporting may increase the demand for female workers, the increase in equilibrium employment will be restricted if the supply of female workers is not forthcoming. We focus on three supply side bottlenecks: unfavorable social attitudes towards women’s employment, labor laws that are more restrictive for women than men, and poor law and order situation as women may be more affected than men by high crime and lawlessness. Thus, our null hypothesis is that the positive relationship between exporting and female employment is much stronger (more positive) when social attitudes towards women’s work are more favorable, labor laws are less discriminatory against women workers, and the law and order situation is more business friendly.

Further, as argued above, exporting increases women’s employment more when relative to non-exporters, exporters use female workers more intensively than male workers. To test for this prediction, we follow the related literature and classify industries by their dependence on female workers. The estimates for the dependence on female workers are taken from Do et al. (2011) and based on UNIDO data. The testable hypothesis is that the positive relationship between exporting and female workers is stronger (more positive) in sectors that rely more on female workers.

# **3. Data and main variables**

The main data source we use is firm-level surveys for 91 (mostly developing) countries. These surveys were conducted by the World Bank’s Enterprise Surveys (ES) between 2006 and 2017. The ES are nationally representative surveys of the non-agricultural private sector of the economies. A common sampling methodology, stratified random sampling, is followed in all the surveys together with a common questionnaire. For each country, the sample is stratified by industry, firm-size, and location within the country. Weights are provided in the survey and used 8
12 1966/67 in the former Western state, put the concentration coefficient (or Gini) at 0.47. Adeboye in a survey of 1635 households conducted in 1967 in all states except three, of the then Eastern Region, found a concentration ratio of 0.58. A number of scholars doing cross-national studies have presented various measures of inequality in Nigeria. Adelman and Morris (1971) presented data for Nigeria showing the richest 5 percent accounting for over 38 percent of income in Nigeria and the poorest 20 percent accounting for 7 percent of income in Nigeria. Odafalo (1981) gave the poorest 34 percent of taxpayers about 7 percent of income and concluded that the degree of inequality in Nigeria was widening.

There has been substantial inquiry into the pattern of income distribution in Nigeria. In an edited volume (Bienen and Diejomoah, 1981) many authors address this issue in detail using fragmented studies and national survey, a study which has attracted many criticisms. Bienen estimates that the national income inequality coefficient has moved from 0.5 in 1960 to 0.7 in 1975/76. He also speculates the worsening of it with the oil boom. There have been studies indicating the pattern of income distribution as far back as 1960 by Adelman and Morris (1971) and Vielrose (1963), although due to different methodologies and sample differences the figures do not compare very well. Anusionwu (1981) estimated income distribution by state using public sector employees for 1976 and gives Gini coefficients of 0.442 for Oyo, 0.494 for Niger, 0.496 for Bendel, 0.37 for Cross River and 0.524 for Sokoto. Most of the studies agree that rural inequality is similar to urban inequality. Aigbokhan (1988), who did the other major study on income distribution shows a decline in income inequality from 0.51 in 1960 to 0.37 in 1980 using consumer surveys. Studies by Collier (1983) and Bevan et al (1988) also provide estimates of changes in
While most firms pay reasonable rates, a few pay extremely high interest. For the large majority interest rates vary from less than 5 percent per year and to 50 percent per year, and the distribution of firms along this range is quite uniform. However around 8 percent of firms pay over 50 percent interest and about 4 percent pay over 100 percent. These rates are always charged by informal lenders ( _prestamistas_ ), who typically charge daily interest rates. Not surprisingly, there is a negative relationship between firm size and the interest rate, although among the approximately 10 percent of firms in the EMES sample which pay interest rates in excess of 100 percent, the largest share corresponds to firms with 11-50 employees.

# **2.5 Informality**

The EMES survey captures seven distinct but related dimensions of informality. These include four sets of mandatory regulations: three dichotomous variables that take a value of 1 if a firm has a tax identification number (RUC _)_ , a municipal license, and requests receipts on all its purchases, and a continuous variable which measures the percentage of the firm’s employees registered with the Ecuadorian Institute of Social Security (IESS). The survey also records the percentage of firm’s employees with written contracts; although this is not a legal requirement as verbal contracts are recognized on an equal basis, the use of written contracts is more indicative of firms which comply with a broader set of regulations, offer more worker protections, and in particular is highly correlated with affiliating employees to IESS.<sup>6</sup> Furthermore, the EMES considers two additional dimensions which are not mandatory for most firms but which reflect having reached a higher stage of development: being incorporated through a public notary and registered in the official registry ( _registro mercantil_ ).

**Figure 5: Formality profile of firms**

<!-- Start of picture text --> by type of regulation (percent of firms in compliance) by sector of economic activity (4-criteria index
time. This is because the two competition variables are close substitutes and intended to capture the same phenomenon. Table A13 and Table A14 in the online appendix provide the regression results. The tables show that the qualitative nature of the results for the various interaction terms discussed above remain unchanged.

# **6. Conclusion**

Rapid globalization over the last few decades has brought numerous economic benefits. However, it has also raised concerns about how vulnerable sections such as female workers are impacted. Theory suggests that several avenues through trade may impact female workers, but these come with important caveats. Empirical evidence on the issue is mixed. It is also limited, especially for the case of developing countries. The present paper attempts to fill this gap in the literature. It does so by using firm-level survey data for 91 (mostly) developing countries to estimate the relationship between exporting activity and the share of females in total workers in firms. We pay close attention to endogeneity concerns. We also test for several predictions of the theoretical models, which helps raise our confidence against endogeneity concerns.

The results show that there is a large positive impact of higher exports (to sales ratio) on the proportion of female workers. Further, consistent with theoretical predictions, this positive relationship is much larger (more positive) in industries that rely more on female workers, in country-industry pairs where domestic competition is low, in countries where social attitudes and labor laws are more favorable towards women’s work, and when the law and order situation is better.

Several questions remain to be answered. We highlight a few of them to motivate future research in the area. First, our results show that exporting activity benefits females in terms of jobs, 29
v) changes in price of food relative to non‐food. All these macroeconomic inputs are generated in 2014 for both scenarios: business as usual (BaU) and crisis. Additionally, we include in the crisis scenario a series of assumptions for IDP and IS‐ affected areas related to assets, services from dwelling as well as employment and labor and non‐labor income.

## **Changes in aggregate and economic sectors GDP**<sup>**17**</sup>

The aggregate macro‐economic and sector‐specific growth rates for Iraq are shown in Table 1 . The BaU estimates assume the same pattern and trend of sectoral and overall growth in the 2013 to 2014 period as was measured in the 2012 to 2013 period. The estimates for the 2014 crisis year are from the official estimates produced by the Iraqi Central Statistics Organization. The latter estimates imply a negative 6 percent growth rate of GDP for Iraq for 2014, which incorporates the macroeconomic shocks related to war against IS and the oil price decline. Relative to a BaU scenario, where GDP would have grown at a positive rate of 9 percent, the magnitude of the macro shocks on GDP imply a 15 percentage point reduction in total economic activity.

The biggest sectoral contraction is in manufacturing and construction, primarily due to a fall in construction, which employs almost 14% of all Iraqi workers and where most of the poor are employed.

> 17 Macroeconomic data and projections were provided by CSO – GoI (March 2014).

11
Policy Research Working Paper 6030

# **Abstract**

This paper analyzes the impact of two distinct shocks stemming from the cross-border transmission of the 2007-2009 crisis on credit availability for small firms. The paper uses data from AccessBank Azerbaijan which was affected in its liquidity position during the second and third quarters of 2008 by delays in its refinancing. The Azeri real economy was hit by the global crisis from the fourth quarter of 2008 onwards with a combined decline in oil prices, exports, remittances, and domestic demand. Therefore, a pure supply side shock con be contrasted with a real economy shock that hit exactly when the bank’s funding position strengthened again. The paper finds that during the _funding shock_ (potential) borrowers are discouraged from applying for loans. However, for those applications made, the likelihood of loan approval is not affected. The _real economy shock,_ in contrast, reduces the approval likelihood for SME loans in particular, while agro and micro loans are considerably less affected. Finally, bank relationships increase credit availability in good as well as in bad times.

This paper is a product of the Finance and Private Sector Development Unit, Africa 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://econ.worldbank.org. The author may be contacted at gberg@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
to provide effort than hired labor. 27 They share in farm risk, and can be employed without incurring hiring or search costs. These attributes underlie the general superiority of family farming over large-scale wage operations, manifested empirically in an inverse relationship between farm size and productivity. A large number of studies based on aggregate, or cross-sectional, and panel data have confirmed the existence of the inverse farm-size productivity relationship for all but the smallest farm size classes (Berry and Cline 1973, Carter 1984, Benjamin 1995, Newell et al 1997, Kutcher and Scandizzo 1981, Olinto 1995, Burgess 1997, Udry 1997).28 Thus, unless there are other countervailing forces, one would expect land markets to transfer land from large to small producers. We turn now to discuss these countervailing effects.

> 2 Exceptions are limited to cases of highly specialized machinery, specialized livestock production, or plantation crops where economies of scale are transmitted from the marketing to the production stage.

> **26** However, the supervision advantages of pwner-operators have in many cases motivated large processors to contract production out to smallholders under outgrower or contract farming schemes, often providing credit in kind as well as technical assistance (Glover 1990).

> **27** Empirical evidence confirms that family labor is more productive than hired labor, and that the intensity of supervision by family members affects the performance of hired labor (Frisvold 1994).

> **28** Bhalla and Roy (1989) and Benjamin (1992) have shown that from cross-section analyses (e.g. Berry and Cline 1973, Carter 1984, Newell et al 1997, Kutcher and Scandizzo 1979) tend to overestimate the productivity advantage of smaller farms if soil quality is not specifically accounted for.

17