rafmacalaba/datause-encoder-data huggingface dataset:
in total observed earnings inequality ranges from 14 percent to 16 percent across the gender spectrum; the national average is 15.6 percent (table 3, column 4). In urban areas, the overall opportunity share in total earnings inequality ranges from 7 percent to 10 percent across gender, and the average in urban areas is 9.4 percent (table 3, column 4). Based on the parametric method, it appears that inequality of opportunity in earnings in rural areas is marginal; the average in rural areas is less than 2 percent. Inequality of opportunity in earnings therefore appears, at least in the case of the Democratic Republic of Congo, to be an urban phenomenon.

**<u>Table 3: The contribution of unequal opportunities to earnings: MLD and Ratios</u>**

||_Total observed_<br>_inequality (MLD,_<br>_factual)_|_MLD estimate_<br>_(CFD)_|_Inequality of_<br>_opportunity level_|_Share in Total_<br>_observed_<br>_inequality_|
|---|---|---|---|---|
||_(1)_|_(2)_|_(3)_|_(4)_|
|Full sample|||||
|All|0.635<sup>***</sup>|0.535<sup>***</sup>|0.0991<sup>***</sup>|0.156<sup>***</sup>|
||(0.014)|(0.012)|(0.007)|(0.009)|
|Male|0.618<sup>***</sup>|0.515<sup>***</sup>|0.103<sup>***</sup>|0.167<sup>***</sup>|
||(0.019)<br>|(0.014)<br>|(0.010)<br>|(0.012)<br>|
|Female|0.567<sup>***</sup>|0.487<sup>***</sup>|0.0796<sup>***</sup>|0.140<sup>***</sup>|
||(0.022)|(0.016)|(0.009)|(0.013)|
|Urban sample<br>All|0.618<sup>***</sup>|0.559<sup>***</sup>|0.0583<sup>***</sup>|0.0944<sup>***</sup>|
||(0.016)|(0.016)|(0.008)|(0.011)|
|Male|0.556<sup>***</sup>|0.501<sup>***</sup>|0.0549<sup>***</sup>|0.0987<sup>***</sup>|
||(0.021)<br>|(0.020)<br>|(0.010)<br>|(0.016)<br>|
|Female|0.581<sup>***</sup>|0.537<sup>***</sup>|0.0446<sup>***</sup>|0.0767<sup>***</sup>|
||(0.029)|(0.028)|(0.010)|(0.016)|
|Rural sample<br>All|0.393<sup>***</sup>|0.386<sup>***</sup>|0.00659<sup>***</sup>|0.0168<sup>***</sup>|
||(0.009)|(0.010)|(0.002)|(0.004)|
|Male|0.386<sup>***</sup>|0.379<sup>***</sup>|0.00698<sup>**</sup>|0.0181<sup>**</sup>|
||(0.011)<br>|(0.012)<br>|(0.002)|(0.006)|
|Female|0.333<sup>***</sup>|0.331<sup>***</sup>|0.00211|0.00633|
||(0.012)|(0.012)|(0.002)|(0.007)|

_Note:_ MLD = mean log deviation. CFD = counterfactual distribution. Bootstrapped standard errors in parentheses based on 99 replications.<sup>*</sup> _p_ < .10<sup>**</sup> _p_ < .05<sup>***</sup> _p_ < .001 Table 4 assesses the roles of individual circumstance variables in the preceding results. It basically presents the MLD coefficients for factual earnings and counterfactual earnings, obtained by equalizing each circumstance variable in turn, while controlling for others as elaborated in equation (13). In a similar fashion as in the case of the estimates in table 3, the shares of each circumstance-specific opportunity in total observed inequality are also reported. The estimates of the shares of circumstance-specific opportunity in total inequality should be interpreted as descriptive evidence. Because of the fact that, if any unobserved circumstance variable is correlated with the individual (observed) circumstance variables, then the estimates are likely to be biased (Ferreira and Gignoux 2011; Singh 2012).

19
Table 1.752 <!-- Start of picture text --> Japanese Trade with other Asian Countries<br>1892 1902 1912 1925 1935<br>£000 Share £000 Share £000 Share £000 Share £000 Share<br>Exports _<br>Prmary Products 1,518 46% 3,701 33% 7,992 26% 20,186 18% 18,208 16%<br>Manufactured Goods: 1,550 47% 7,115 64% 21,638 71% 86,706 75% 91,288 81 %<br>Textiles 211 3,631 13,560 57.791 45,354<br>Other Light Industrial Goods 559 2,118 4,471 _ 13,8981 13,861<br>Heavy Industrial Goods 780 1.366 3,607 13.017 32.093<br>Total 3,270 100l 11,051 100I 30,527 100l . 115,240 100% 113,170 100O<br>Imports<br>Primary Products: 3,940 89% 11,660 94% 31.031 94% 138,636 95% 81.220 89%<br>Food 2,144 4,300 12,773 63,619 36,725<br>Raw Material for Textiles 1,600 6,265 14,376 52,591 19,558<br>Other Raw Material 196 1,095 X 3,882 22,426 24,937<br>Manufactured Goods 480 11% 669 5Y 1,579 5% 6,666 5% 9,764 11%<br>Total 4,435 100Y 12,418 100Y4 32,887 100Y 146,184 100%- 91,710 100G<br>Source: Sugihara (1990: Table 3,133); Yukizawa Kenzo and Maeda Shozo, Nihon Boekino Choki Tokei (Japanese Trade<br>Statistics Reaggregated by Commodity and by Basic and Major Region). Kyoto, Dohosha, 1978.<br>Notes: Total includes special category trade. Foreign Exchange Rate see Yamazawa Ippei and Yamamoto Yozo,<br>Boekito KokusaiShoji (Foreign Trade and Balance of Payments), LETS Vol. 14, Tokyo, ToyoKeizai Shimposha, 1979.<br><!-- End of picture text --> Table 1.6 shows that Japan's trade in the early 1880s was primarily with the West, which was the case for other Asian countries as well. In Japan's case, this trade consisted of exports to the West of primary products and semi-manufactured goods and imports of manufactured goods from the West (Sugihara 1990). However, by the end of the 1 9 th century this pattern had changed so that Japan's trade with Asia rose to make up about half its total trade. This proportion remained unchanged until the late 1930s when intraAsian trade in general began to decline. The breakdown of Japan's trade with Asia also changed over that period. Table 1.7 above shows that in 1892 Japan was exporting an equal proportion of primary products and manufactured goods to Asian countries but by 1935 only 16 percent of its exports were primary products while 81 percent were manufactured goods. The proportion of imports to Japan from Asia remained about the same over that period, i.e., around 89 to 95 percent were primary products.

Sugihara (1990) argues that the rise in Japan's proportion of intra-Asian trade is evidence of its function as an "engine of growth of intra-Asian trade." She accounts for this by pointing out the following: (1) Chinese and Indian merchants carried most of Japan's trade with Asia via their intra-Asian network during the early 1900s, (2) Japan knew, better than the West, how to produce goods of a certain quality and price that were suitable for the Asian market (her previously mentioned "culture neutralization"), and (3) Japan adopted Western technology faster than other Asian countries which gave it an advantage in the production of manufactured goods for export to Asia.<sup>53</sup> 12
workforce and adequate infrastructure (Butollo 2021; Arunyanart et al. 2021).

As discussed in Kilic Celik, Kose, and Ohnsorge (2023), potential output growth is expected to slow in many EMDEs in the coming decade amid unfavorable demographics and slowing investment and productivity growth. One way in which policymakers in EMDEs can boost long-term growth of output and productivity is by promoting trade integration through measures to reduce trade costs.

Our study examines the following questions. First, what is the link between trade growth and long-term output and productivity growth? Second, what are the prospects for trade growth in the coming decade? Third, how large are trade costs? Fourth, what are the correlates of trade costs? And fifth, which policies can help to reduce trade costs?

Our study contributes to the literature in a number of ways. First, it expands on World Bank (2021b) with a new, comprehensive review of the theoretical and empirical literature on the links between trade and output growth. Second, it presents an event study of the evolution of trade in goods and services through global recessions, including the pandemic-induced global recession of 2020.

Third, our study revisits an earlier literature that reported estimates of trade costs and their correlates (Arvis et al. 2016; Novy 2013; World Bank 2021b). It uses estimates of the costs of goods trade for up to 180 countries (29 advanced economies and 151 EMDEs) from the World Bank/UNESCAP database for 1995-2019. The drivers of the costs of goods trade, which accounts for about 75 percent of world and EMDE trade in goods and services, are estimated econometrically. Our study also quantifies the contribution of one type of services trade—logistics and shipping services—to the costs of goods trade. In addition, our study goes further than previously published research in assessing the role of trade policy—tariffs, participation in trade agreements—in trade costs.

Fourth, our study builds upon its analytical findings to discuss policy options for lowering trade costs. In particular, it offers scenarios indicating the potential reduction in trade cost associated with a menu of policy measures.

Our study offers the following findings.

First, the theoretical literature indicates that international trade boosts the long-term growth of output and productivity by promoting a more efficient allocation of resources, technological spillovers, and human capital accumulation. The empirical literature supports the theory by finding statistically significant positive relationships between openness and output growth, although they may be conditional on the presence of sound institutions and a supportive business environment in exporting countries. Overwhelmingly, empirical studies find a positive impact of trade on productivity growth.

Second, the COVID-19-induced global recession of 2020 triggered a collapse of global
# **1. Introduction**

Infrastructure capital, understood as including transport related facilities (roads, railroads, ports and airports), water and waste water treatment facilities, telecommunications, and energy generation, transmission and distribution, is often mentioned as a prerequisite for the success of development policies and has therefore been for some time an important topic on the agenda of politicians and development practitioners that endow it with many virtues. Since the late 1980s, economists have produced hundreds of papers, mostly empirical, on the subject, mostly making use of macro level data, i.e. cross country or cross state data. To date, despite all this accumulated evidence, the link between infrastructure availability and economic productivity or growth is still subject to considerable uncertainty and debate.

This survey takes stock of the existing macro level literature in order to see how 15 years of sustained research have enhanced our understanding of this major development issue. To assess these contributions, it provides a general framework that spells out the relevant terms of the controversy on the real effect of infrastructure on growth in the context of an aggregate production function. It then signals in the context of this framework what are the relevant empirical questions to be addressed. This guides the systematic review of a number of empirical studies, which seeks to identify to what extent answers have been provided to these key questions and discusses the main econometric challenges to the identification of the effect of infrastructure on output and productivity. Finally, building on related existing research, in particular in contract theory and political economy, it spells out several promising research avenues.

## _Infrastructure: A Review of Issues_

Infrastructure matters first because it provides key final consumption items to households, particularly water and to a lesser extent energy and telecommunications. Overall, a rule of thumb is that between one third and one half of infrastructure services 2
Policy Research Working Paper 5789

# **Abstract**

In a crisis, do employers place the burden of adjustment disproportionately on female employees? Relying on household and labor force data, existing studies of the distributional impact of crises have not been able to address this question. This paper uses Indonesia’s census of manufacturing firms to analyze employer responses and to identify mechanisms by which gender differences in impact may arise, notably differential treatment of men and women within firms as well as gender sorting _across_ firms that varied in their exposure to the crisis.

On average, women experienced higher job losses than their male colleagues _within_ the same firm. However, the aggregate adverse effect of such differential treatment was more than offset by women being disproportionately employed in firms hit relatively less hard by the crisis. The null hypothesis that there were no gender differences in wage adjustment is not rejected. Analyzing how employer characteristics impact labor market adjustment patterns contributes to the understanding of who is vulnerable in volatile times.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group; and the Chief Economist’s Office, Financial and Private Sector Development 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 author may be contacted at mhallward@ 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
Harmon and Lydon (2001) identify higher returns to education in more open countries. Several country studies that analyze the e¤ect of trade on relative wages of skilled and unskilled workers conclude that technology transfer is the most likely reason for the increase in wage inequality (e.g. Robbins (1994, 1995), Hanson and Harrison (1994)).

Still, observing higher relative wages in more open economies does not allow to conclude that trade enhances human capital accumulation since relative wages are likely to be a¤ected by country speci...c factors, such as technology, supply of human capital or labor market regulations. Direct evidence on the relation between trade and human capital accumulation is far from conclusive. Using a cointegration analysis, Chuang (2000) ...nds a bidirectional Granger causality between exports and the share of individuals who have attained higher education in Taiwan. Alcala and Ciccone (2001) conclude that trade increases productivity in the cross-country context, but ...nd no statistically signi...cant association between openness and the average level of human capital, as measured by years of education. None of these studies analyzes the e¤ect of trade on on-the-job human capital accumulation.

This is not the ...rst study using data on US immigrants in order to deduce information about their country of origin. Hanushek and Kim (1999) and Bratsberg and Terrel (2002), for example, analyze the e¤ect of home country school quality on earnings of US immigrants. Hanushek and Kim (1999) ...nd a strong and positive e¤ect of international math and science test scores on earnings and returns to education of US immigrants. Bratsberg and Terrel (2002) conclude that holding per-capita GDP constant, immigrants from countries with lower pupil-teacher ratios and greater expenditures per pupil earn higher returns to education in the US. Borjas (1998) provides empirical evidence about the e¤ect of source country characteristics on US immigrant quality. This is the only study to my knowledge that relates openness to earnings of US immigrants. He ...nds no signi...cant e¤ect of openness on the log entry wage of US immigrants when controlling for country ...xed e¤ect and/or educational attainment. None of these studies analyzes the e¤ect of home country characteristics on on-the-job human capital accumulation of US immigrants.

4
<!-- Start of picture text --> 58.6<br>Pe<br>6 47.6<br>co 42.3 54.5 47.1<br>os<br>vs=¢ 35.1 45.5<br>os 41.6<br>ee 38.3<br><2 33.7<br>ome)<br>sa<br>8<br>3. 25.7 24.6<br>a<br><!-- End of picture text --> NRVA 2007-08 <!-- Start of picture text --> NRVA 2011-12 ALCS 2016-17 IE-LFS 2019-20<br>—e Rural =—@ National —®= Urban<br><!-- End of picture text -->
2 In response to rapidly growing foreign populations, many countries introduced 100% mechanisms to stem the inflow of 80% - .X workers and encourage the t 60% 60% . 40% --employment of nationals; 200% measures typically included permit 0% requirements for foreign workers Bahrain Saudi as well as incentives to promote job creation targeted specifically Source: Stalker (1994). to nationals. Some of these <!-- Start of picture text --> Figure 1<br>Foreign Labor % of Labor Force in GCC Countries, 1990<br>100%<br>80% - .X 1<br>t 60% 60% .<br>40% --- ~ - -<br>200%<br>0%<br>Bahrain Saudi UAE Kuwait Oman Qatar<br>Arabia<br>_ _ I m Foreign N National I<br>- - - -<br><!-- End of picture text --> policies actually contributed to the proliferation of foreign workers, however. In Kuwait, for example, the decision to create public sector jobs for nationals led to high wage expectations among Kuwaitis, due to relatively high wages and generous benefits in the public sector, and insufficient labor supply to the private sector. On the demand side, employers must finance the military service obligations of Kuwaiti males, rendering foreign workers relatively less expensive. These price and quantity controls effectively distorted the labor market in Kuwait such that private sector labor demand had to be met by an everpresent supply of cheap foreign workers. In Bahrain, all foreign workers in the public sector other than those judged to be indispensable were replaced with Bahraini nationals. High public sector compensation compared to the private sector led to high reservation wages and queuing for govemment jobs by Bahraini nationals, generating even greater demand for foreign workers to fill unskilled jobs despite the additional costs of work permits. Across the region, the composition of the pool of foreign workers has evolved considerably over time, and the available supply has increased in conjunction with global:ization. Moreover, policies to limit foreign labor face considerable challenges because they may be counterproductive with respect to economic growth. The tension between competing objectives to generate employment through sustainable economic growth on the one hand, and to limit the number of expatriate workers on the other hand, has impeded the efforts of GCC policy makers on both fronts.

Are there lessons from other regions that provide insight into effective labor management with respect to foreign labor? Among the emerging East Asian economies, Singapore and Malaysia have experienced sustained and robust economic growth with considerable reliance on foreign labor. As labor importers, their policy experience and labor market outcomes are instructive for policy makers in the GCC countries. This paper analyzes the policies used to manage foreign labor in Singapore and Malaysia
Table 6: Composition of Costs of Visits (percentage and total costs)

||||TYPE|||LOCATION<br>Other<br>|||
|---|---|---|---|---|---|---|---|---|
||Public|Private|Religious|NGO|Capital|Urban|Rural|Total|
|Consultation (%)|15.8|19.2|18.9|14.8|16.7|22.6|13.6|16.9|
|Laboratory Tests (%)|10.0|21.4|6.1|0.7|18.8|3.2|1.9|12.0|
|Medication (%)|74.2|59.4|75.0|84.5|64.5|74.1|85.1|71.1|
|Total costs(FCFA)|2375|4987|1601|1397|4320|1191|1276|2516|

Source: Chad 2004 QSDS and authors’ calculations.

Examining the composition of costs of medical visits to health centers, expenditures on medication represent about 3⁄4 of patients’ total costs. Medical consultation costs represent less than 14% of the total cost of a visit in rural areas compared with 23% in urban areas other than the capital. As for laboratory tests, it is only in the capital that they represent a significant portion of patient expenditures (19%).

# **5.4 Patients’ Knowledge of Alternative Care Availability**

Before examining the choice of health facilities by patients and in particular the patterns of bypassing, it is useful to examine patients’ knowledge of health care services available.

As shown in Table 7, about 39% of patients report that health care providers (either formal or informal) other than the one they visited the day of the survey are located close to their home. With respect to the modern health sector only, about a quarter of the patients report having access to alternative health centers or hospitals.

It is interesting to note that the capital city offers not only more modern health service providers but also more informal providers. Indeed, 28% of patients there report having informal care in their neighborhood versus 19% in rural areas.

11
The scatter plot of alpha and sectoral TFP growth below shows a statistically significant negative correlation between these two variables in India and Brazil. Sectors in India are marked with “1”; Brazil “2”. The TFP sectoral growth is based on the median value of firms surveyed in that sector; the alpha is taken from the sectoral production function estimation. The within country sectoral correlations with alpha is also negative (for both India and Brazil) but not statistically significant.

The policy implication from the above analysis is evident: exposing firms to the best practices – for Instance, through market oriented policies -- is key to generate conditions that promote aggregate growth. On the opposite side, rigidities that block the natural process of birth, expansion, and death of plants and firms, and the reallocation of resources among economic units, impede growth and limit development. Indeed, flexibility at firm and national level is key for growth. Market economies restructure continuously as a response to changing conditions. Our results, and those of a growing literature based on longitudinal databases at the micro level, suggest that productivity growth at the aggregate level is closely linked to the ability of the economy to efficiently reallocate inputs and outputs across firms. Thus barriers to this efficient reallocation process reduce aggregate efficiency and growth. For instance, a production subsidy to incumbent firms allows inefficient plants to stay longer in business.

At the same time, more efficient firms that would have entered the market are left out. Financial restrictions, trade barriers, firm entry costs, inefficient bankruptcy procedures, bureaucratic red tape, tax burden, labor regulations, and the lack of human capital for technology adoption, all distort the natural process of resource reallocation. Chang et al (2005), for instance, provide empirical evidence of a link between growth and measures of market flexibility and ease of entry and exit, whereas Hopenhayn and Rogerson (1993) and Bergoeing, Loayza and Repetto (2004) develop theoretical models showing that this link is a result of the ability of the economy to easily reshuffle resources towards more productive uses.

# **4.     What Determines TFP?**

We now look into the determinants of TFP on firm level. The following regressions use lnA or TFP (log form) as derived from the firm level regressions as the dependent variable (see equation (5)).

lnA = lnY – α lnK – β lnH (5) 16