rafmacalaba/data-use-mentions-extended huggingface dataset:
significance are very similar to the results in panel A, so that we still obtain the same results even holding occupation fixed.

The quantity numbers we have are for new contracts issued. Typically new hires are 38% of the total contracts issued each year, with rehires constituting the remainder. Micro data on rehires was not available from the POEA, preventing us from examining the wages for this group. Nevertheless, annual destination country level data on total quantities of migrants are available from 1998 to 2009 in the POEA’s Compendium of Overseas Foreign Worker Statistics (Philippine Overseas Employment Administration, 2005-2009). We subtract the total new hires from our micro data from these totals to obtain data on rehire numbers by year.

We use this rehire and total contract worker data to examine the robustness of our migrant quantity results to the measure of migrant flows used. Table 3 presents the results. First, column 1 re-estimates equation 1 on our micro new hire data over the shortened time period 1998-2009. The point estimate suggests an even higher elasticity of quantities to GDP over this shorter period, but we cannot reject equality with our point estimate over the full sample. Columns 2 and 3 then show the same elasticity for rehires and for total migrant contract workers respectively. The point estimates are positive and significant in both cases, and we cannot reject equality of the total and rehire responses.

The stock of migrant workers at origin depends on both the flows of migrant workers, and how long these workers stay. The elasticity of the stock of contract workers with respect to GDP may therefore deviate from that of the flow if the duration of contracts varies with economic conditions at origin. Our database contains the duration of each new contract issued, and in column 4 of Table 3 we test whether the contract length (in months) varies significantly with GDP. The effect is statistically insignificant, and the point estimate is small, suggesting a 1 percent increase in GDP only increases contract duration by 0.16 months. As a result, we
out in cooperation with CAPMAS (Anker and Anker 1989). The survey indicated that in the oneweek reference period 12% of Egyptian women participated in wage or salary employment, 37% participated in market work, and nearly 80% participated in “standard” work, which is the equivalent of the extended work definition (market plus subsistence work).

In October 1988, a special round of the Labor Force Survey was carried out (Fergany 1990). The special round adopted the resolution of the 13th ICLS held in 1982, which states that “persons engaged in the production of economic goods and services for own and household consumption should be considered in self-employment” and therefore as a labor force participant (Anker 1983; ILO 1982). However, there was no way of operationalizing the 13th ICLS condition for this kind of work to count as employment, which stipulates that such work should only be included in employment “if such production comprises an important contribution to the total consumption of the household.” In practice, all production and processing of primary commodities for purposes of own household consumption ended up being included.<sup>4</sup> Furthermore, no separate measures for market and subsistence work were reported. As shown in Figure 1, this extended definition of employment resulted in a large increase in the measured female labor force participation rate to 31%, with the rural rate reaching over 41%. This definition was maintained in theory in subsequent rounds of the LFS, but its application gradually waned as less emphasis was placed on the inclusion of subsistence work. As a result, the measured FLFP rate in the LFS declined to 22% in 1990 and 17% in 1992, stabilizing at that level for a couple of years and then declining further to 15% in 1997. The measured FLFP rate remained roughly at that level through 2003, with the urban rate exceeding the rural rate in 2001 and 2002 for the first time since the early 1980s.

In the meantime, the first wave of the
who were not employed were nonetheless looking for work and in the labor force, so that labor force participation rates were quite similar in 2001, 2005 and 2010 for women under 45. By 2010, however, the CULS suggests a sharper drop in labor force participation among urban women over age 45 than we observed in earlier years.<sup>10</sup> The decline in older women’s labor force participation raises an important question for labor research in China: Does the decline in women’s employment reflect a resurgence of gender discrimination in post-reform China or the effects of increases in household wealth and the ability of women to exit the labor force at a younger age? Differences across genders in mandatory retirement ages likely creates an institutional bias against women’s employment. Even in the absence of discrimination, the employment decision of older women in urban China reflects a constrained choice. Women may return to work as consultants or in self-employed activities after reaching mandatory retirement age, but retired women are frequently receiving pensions, which raises reservation wages for new employment. Those urban women uninterested in working in typical self-employed activities held by blue collar workers (e.g., nannies or housekeepers), may choose to stay out of work if their pension incomes are sufficient.

Earlier research on labor force participation in China has noted the drop in employment rates of urban residents, and urban women in particular (Cai et al, 2008; Maurer-Fazio et al, 2011) and attributed the drop to the effects of state sector restructuring after 1997. Restructuring reduced the state sector through two mechanisms: for younger state-sector workers, a special one-time urban layoff ( _xiagang_ ) program provided up to three years of living subsidies (and continued pension and health insurance contributions), as well as training and job placement assistance through reemployment centers. Workers within five years of retirement age were encouraged to take early retirement with pension benefits. As women were much closer to retirement age than men, particularly blue collar workers facing retirement at age 50
expenditure in a year from 1995 to 2021. At the same time, these economies have been gaining greatly from international trade. However, no comprehensive study exists on how much they have gained from import variety growth.

We use highly disaggregated import data from 1995 to 2021 to estimate the elasticities of substitution for 4,537 imported goods on average for all 28 countries. These elasticities allow us to construct a comprehensive measure of the welfare gain using the seminal works by Feenstra (1994) and Broda and Weinstein (2006). The welfare gain as a result of growth in import variety during the period amounts to an average of 5.49% of GDP. We found that African countries on average gained more than Asian countries excluding Bhutan during the period. This indeed confirms the finding in the literature that the welfare impact of import variety growth is greater in developing countries.

The evidence from this paper indicates that for small and transitioning economies, the establishment and expansion of trade linkages can be a significant source of welfare. This aspect is often overlooked in discussions about the effects of globalization and economic integration.

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2 DASGUPTA AND GROVER

# **1. Introduction**

Geography plays a significant role in determining the distribution of economic activity across space. In particular, the suitability of a region to engage in domestic and international trade is critical in influencing spatial concentration of people and economic activity (Henderson et al., 2018). Recent trade liberalization episodes in some countries have enhanced spatial concentration within countries. In China, for instance, the decline in international trade costs enabled export-oriented industries to emerge close to ports at the expense of other regions (Cos ̧ar and Fajgelbaum, 2016) and pushed remote regions to specialize in agricultural products (BaumSnow et al., 2017).<sup>1</sup> This has inevitably led many researchers to conclude that greater openness to trade may lead to skewed regional development (Kanbur and Venables, 2003).

Using establishment-level data from the Indian organized manufacturing sector covering the period 1989-2009, we examine whether a decline in _external_ trade costs, triggered by the trade liberalization episode of the 1990s, affected the spatial distribution of economic activity, and the role that _internal_ trade costs played in shaping such spatial dynamics. We then explore whether the subsequent decline in internal trade costs brought about by the large scale construction and upgrade of highways during 2000s, the Golden Quadrilateral (GQ) project, may have affected spatial development.

To analyze how internal geography interacts with international trade to affect regional growth, we group Indian districts into three regions, based on their distance from the nearest major port (air or sea): the primary region (districts within 200 kilometers of the nearest port), the secondary region (districts between 200 to 400 kilometers from the nearest port) and the interior region (districts located farther than 400 kilometers from the nearest port). At the outset, we note three key stylized facts on spatial development in India.

**STYLIZED FACT 1:** _During 1989-2009, organized manufacturing activity was highly concentrated in a few districts, mainly in the primary
respectively. However, the peak is not indicative of the impact of the shock over the entire year. Instead, we assume a loss equal to the average over 2020, i.e. 8 _._ 3, 9 _._ 5 and 6 _._ 7 percent respectively (see Web Appx. Section D for details). **5.2.2. Results** For the HICs, the employment disruption is of 8 _._ 3 percent, and the schooling disruption is of 21 percent (south east of point C in Fig. 5(a)). For the MICs, the employment disruption is of 9 _._ 5 percent, and the schooling disruption is of 33 percent (middle near the right edge in Fig. 5(b)). For the LICs, the employment disruption is of 6 _._ 7 percent, and the schooling disruption is of 28 percent (point to the west of point C in Fig. 5(c)).

The welfare impact equals 2 _._ 5 percent of steady state income in perpetuity in the HICs, compared to 2 _._ 2 percent in the MICs and 1 _._ 5 percent in the LICs (hence 2 _._ 1 percent on average in developing countries).<sup>41</sup> After ten years, when the direct impact of the shock has worn off, we get 1 _._ 2 percent in the HICs, compared to 1 _._ 2 percent in the MICs and 0 _._ 7 percent in the LICs (1 _._ 1 percent on average in developing countries).<sup>42</sup> LICs are,

> 41This is equivalent to a one-off hit of 63, 55 and 36 percent of income respectively. Alternatively, this is equivalent to $15 _,_ 478, $3 _,_ 478 and $419. Overall, this amounts to 59 percent of
22

**Figure 4:** Density of bilateral migration stocks among country-pairs with and without visa provisions: developed _vs_ developing destination countries.

<!-- Start of picture text --> Migration to developed countries Migration to developing countries<br>0 5 10 15 0 5 10 15<br>Log of migration stock<br>Migration stock density with visa provision<br>Migration stock density without visa provision<br>.15<br>.1<br>Density<br>.05<br>0<br><!-- End of picture text --> Source: United Nations Population Division and World Bank Deep Trade Agreement database.

**Table 1:** The probability of having visa provision in DTAs.

|Dep var:|Vi|sa|||
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Right wing vote (sh)<sup>_a_</sup><br>GDP diference (ln)|-0.051***<br>(0.004)|0.004***<br>(0.001)||-0.064***<br>(0.005)<br>0.004***<br>(0.001)|
|Schenghen|||0.045***<br>(0.006)|0.012**<br>(0.006)|
|Estimator|OLS|OLS|OLS|OLS|
|Year FE|Yes|Yes|Yes|Yes|
|Country-pair Fixed Efects|Yes|Yes|Yes|Yes|
|Sample period|1990-2020|1990-2020|1990-2020|1990-2020|
|Observations|346,150|210,944|346,150
method is well-suited for evaluation of many customs reforms. The method can exploit the high-quality administrative data that exists in the customs environment. In particular it can capture, and exploit, the complex dynamics observed in the outcome variables of interest. The method also offers more credible treatments of heterogeneity and selection than other _ex post_ evaluation methods. A recent methodology proposed by Dube and Zipperer (2015) offers a robust approach to hypothesis testing that pools synthetic control results across multiple treated units. Among other advances, the pooled approach allows heterogeneous impacts to be estimated across treated units, even as it

> 5 It may seem unusual to use these higher percentiles as measures of uncertainty rather than, for example, the variance or the interquartile range of the clearance time distribution.  The IHC program imposes a default clearance time that mechanically raises the clearance time in the lower half of the distribution for most IHC firms.  In our view reductions in clearance time at the upper end of the distribution are more valuable to the firm than reductions at the low end, so we focus on statistics that inform reductions at the upper end of the distribution.

> 6 Indeed, in this paper we show that DiD is invalid for an evaluation of the impact of the IHC program because the assumption of common trends is violated.

3
(Hale et al., 2020).<sup>6</sup> Figure A. 6 shows the changes in the stringency indices of major countries since the first wave of the pandemic. The stringency index averaged 25; at its highest, the index was 96. Figure A. 7 shows differences in maximum lockdown severity among selected countries.

Figure A. 8 plots three indicators of COVID-19 severity: new cases per million, new deaths per million, and the lockdown stringency index developed by Oxford University. The graphs on the left-hand side in each row display the new cases per million (scale shown on the left axis) and the new deaths per million (scale shown on the right axis). The scales of the two indicators are adjusted to allow the line graphs to have a similar height. The graphs on the right-hand side show the change in policy stringency throughout the study period. We define the start of the pandemic as March 15, 2020 (marked by the red vertical line).<sup>7</sup> As shown in the plots, the new cases per million population and the new deaths per million population mirror each other very well, with the death indicator lagging several days compared to the case indicator. The stringency index, however, does not necessarily follow either the cases or the deaths closely. For example, it rose promptly at the start of the pandemic when the new cases and deaths per million were relatively low compared with the rest of the post-pandemic era. The stringency of the policies then gradually decreases as economies reopen in the summer of 2020. With the arrival of colder weather (around October 2020), the caseload significantly increased. The stringency index rose slightly again while governments were re-imposing restrictions to mitigate the new COVID wave. The Delta variant was first detected in India in December 2020. It spread to other countries and generated another wave of cases in the summer and fall of 2021.

Different regions also show very different COVID-19 severity patterns. At
under the areas of institutional reform, infrastructure investment, credibility and public management, and financial intermediation.

**Table 4. Projected per‐capita growth rate if saving rate remains at 20 % of GDP**

|Productivity<br>growth|Per‐capita GDP growth rate ov|er time (%)|
|---|---|---|
||5 years<br>10 years|25 years|
|0%|0.8<br>0.8|0.7|
|1%|2.0<br>2.1|2.3|
|2%|3.2<br>3.5|4.1|

Consider first the privatization of state‐owned firms. In 1991, over 300 state‐owned firms were identified as candidates for privatization in Egypt (Law 203). Evidence suggests that firms privatized under the new law enjoyed a substantial increase in productivity. In effect, this improvement in productivity was observed with great strength during the 1990s, the period when most of the privatization wave took place: privatized firms increased investment expenditures, profitability, and overall efficiency (Omran 1997). Related to this point is the observation that, historically, a unit of investment by the private sector is almost invariably more productive that a unit of public investment (World Bank 2008). Today, many firms identified by Law 203 as candidates for privatization still remain publicly owned—the privatization wave was temporarily stalled in the late 1990s, but partially resumed in mid‐2004. In light of the above evidence—and, more generally, worldwide evidence—it is expected that continuing with the privatization effort is likely to promote significant productivity gains.

Analysis of firm‐level data shows that Egypt has experienced substantial progress in labor and total factor productivity between 2004 and 2008 (World Bank 2009). Moreover, the same study reports substantial progress in improving the overall investment climate during these years.
**Figure 1: Employment status among those aged 20-59, by sex**

<!-- Start of picture text --> Men Women<br>3.83<br>9.18<br>20.64<br>6.50<br>72.87<br>86.99<br>Employed Unemployed Out of Labor Force Employed Unemployed Out of Labor Force<br>Men Women<br>3.97 12.63<br>20.03<br>4.91<br>75.06<br>83.40<br>Employed Unemployed Out of Labor Force Employed Unemployed Out of Labor Force<br>2012<br>2018<br><!-- End of picture text --> _Notes_ . The analysis relies on cross-sectional data from the Egypt Labor Market Panel Survey (ELMPS) in 2012 and 2018. This figure presents the employment status of individuals aged between 20 and 59 years old in each survey round. We rely on the market definition of work status, search required (reference 1 week). Expansion weights are used.

We now turn to the sectoral make-up of the Egyptian labor market. We adopt a tripartite classification of private informal, private formal, and public formal sectors. Egypt’s large informal sector is similar in size to those of Mexico and Colombia, each having around 60% of workers employed informally.<sup>5</sup> However, Egypt had a substantially larger public sector, which accounted for over one-quarter of employment. Instead, in 2020, the public sector accounted for 13% of Mexico’s employment<sup>6</sup> and just over 4%<sup>7</sup> of Colombia’s. Other countries at similar level of GDP

> 5 Lanau, S, Rodríguez-Delgado, D., and Toscani, F. 2018. ‘Colombia Selected Issues’. IMF. p 17. Gurría
from 1983 to 2009. The sampling frame for these surveys captures a representative sample of the Indian population, and aggregate figures are calculated based on the sampling weights provided with the data. The surveys lack the ownership fields required to study entrepreneurship, but they do contain information that allows us to model women’s employment in unorganized manufacturing. In the typical survey, 3%-4% of women are employed in manufacturing, with over 60% of women listing domestic activities. We specifically use the designation of the respondent’s employer as an Own Account Enterprise (OAE) to proxy for the unorganized sector. These surveys aid our empirical work in three ways: 13
obviously highlights that Africa remains a very small player in the EPZ market; however, it is broadly in line with the region’s share of global trade and investment.

Virtually no detailed data exist that would allow for a broad analysis of Africa’s performance in EPZs – in terms of investments, exports, and employment – relative to other regions. The only (limited) data available from the ILO’s database (Boyenge, 2007) provides an indication on employment levels in zones. This shows that, as of 2006, zones in Africa and the Indian Ocean (Mauritius, Madagascar, and Seychelles) employed over 1 million workers. This is equivalent to 4% of worldwide zone employment (excluding China; 1.6% including China). However, half of the total employment listed in the ILO database is from one country (South Africa).

Anecdotal evidence suggests that success in African zones (even defined narrowly in terms of scope and time) has been limited to a few countries such as in Mauritius, Kenya, and Madagascar. In many other countries in the region – including Nigeria, Senegal, Malawi, Namibia, and Mali – zones appear to be struggling for a variety of reasons, including poor locational choices, lack of effective strategic planning and management, and problems of national policy instability and weak governance (Watson, 2001). Even where programs have been successful in attracting investment, creating employment, and generating exports, there are concerns over the quality of investment and employment as well as its sustainability. Indeed, the recent experience of Madagascar may highlight the fragility of the economic zones models implemented in Africa to date.

# **3. Defining and measuring “success” in economic zones**

Economic zones are normally established to act as a catalyst for trade, investment, and wider economic growth. Most often they aim to improve competitiveness so as to facilitate the economic transformation of their host countries in a way that is faster or more effective than would be the
Our findings point to several important areas for future research and data collection to inform policy. Nationally representative data at the pre-primary stage are rare in LMICs (Raikes, Sayre, & Lima, 2021), and data are important pre-requisite to evidence-based efforts to address inequality. Longitudinal data on young children and the trajectory of their development in LMICs are also much needed to understand critical points for intervention.<sup>22</sup> Further research on promoting pre-primary quality and the impact of quality interventions on ECD is needed. Most of the evidence on what works to promote teaching quality and learning in LMICs comes from the primary level. For instance, only 8% of studies on education in Africa focused on pre-primary (Evans & Mendez Acosta, 2021). Research exploiting the random assignment of kindergarten students in Ecuador demonstrated that teachers’ classroom practices are associated with higher learning (Araujo, Carneiro, Cruz-Aguayo, & Schady, 2016). At the pre-primary level, play-based learning can be particularly important and effective (Attanasio et al., 2019; Wolf, Aber, Behrman, & Tsinigo, 2019). However, play-based approaches can also face backlash from parents or teachers (Wolf, Aber, Behrman, & Tsinigo, 2019).

In addition, further research with rigorous causal identification strategies is needed to assess whether, when, and how pre-primary may help close gaps in ECD, as well as which specific input improvements would be most effective for improving equity and learning. Efforts to examine the impact of quality pre-primary on child development should therefore include estimates of the quality of children’s home learning environments, given the large impact of home environments on children’s learning and potential role of pre-primary and pre-primary quality in closing gaps.

> 22 The Young Lives study is an example of longitudinal data collection that can shed light on important aspects of ECD and interactions with early environments, although the data were not nationally representative (Young Lives, 2017).

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