rafmacalaba/datause-encoder-data huggingface dataset:
|_2 to 5_|2.80|10.03|2.87|1.94|17.65|
|---|---|---|---|---|---|
|_6 to 10_|1.02|7.98|6.15|7.01|22.16|
|_11 and above_|0.37|7.00|9.53|41.14|58.04|
|**_Total_**|5.35|25.86|18.67|50.11|100.00|

Source: Authors’ calculations based on data from Comtrade.

**Figure 170 Product vs. geographical portfolios**

<!-- Start of picture text --> Average Number of Products per Firm Average Number of Destinations per Firm<br>18 4<br>16 3.5<br>14<br>3<br>12<br>2.5<br>10<br>2<br>8<br>1.5<br>6<br>4 1<br>2 0.5<br>0 0<br>2004 2005 2006 2007 2008 2009 2004 2005 2006 2007 2008 2009<br>PAK BGR COL ECU PER ZAF PAK BGR COL ECU PER ZAF<br><!-- End of picture text --> Source: Authors’ calculations based on data from the Exporter Dynamics Database (World Bank).

Statistics about high-performing exporters, the so called “gazelles”, may be seen as consistent with the above assessment. Indeed, when exploring the characteristics of high-performing exporters, i.e. firms with an annual growth rate of at least 75% for four consecutive years (between 2001 and 2010), interesting patterns are established. It is clear that firms that perform consistently well over this period share a few common characteristics, depending on their size. Those with smaller export values tend to, on average, concentrate growth in a few products (at the HS8 digit level) but are well diversified in terms of destination markets. In addition, the relatively smaller top-performers also export mostly to other South Asian countries. The larger top-performing firms, on the other hand, seem to diversify their exports across more countries and away from South Asia. They also seem to, on average, export more products over the high-growth period.

The next two sections will explore the entry, exit and survival of new exporters using firm and transaction-level data. Studying rates of entry and exit will provide an assessment of the dynamics of firm movements in and out of markets, whether destination or product. On the other hand, survival rates will provide an overview of how well exporters are able to continue and deepen their trade relations across new markets.

29
# **Introduction**

While there are other more prevalent diseases in Africa, the characteristics of HIV/AIDS suggest that its economic and demographic impact will be profound. In the absence of the AIDS epidemic, prime-age deaths would be relatively rare in Africa. Because HIV in Africa is transmitted primarily through heterosexual contact, the epidemic is having a dramatic impact on the mortality of men and women in their prime childbearing and earning years; consequently, the mortality rates of adults 15–50 increase dramatically in areas affected by the epidemic (Ngom and Clark, 2003). Moreover, HIV/AIDS is not restricted to poorer populations. Unlike other major diseases in Africa, HIV/AIDS is prevalent among the better educated and higher income Africans in urban areas, with mixed evidence about the correlation between socio-economic status and HIV. For example, earlier evidence (World Bank, 1999) indicated higher rates among better education/higher income groups, whereas more recent population survey data analyzed by De Walque (2006) does not indicate a correlation between education level and HIV status.

The implications of the epidemic, increased rates of severe illness and prime-age adult mortality, suggests that the disease will have consequences for a host of socio-economic indicators. This paper adds to the literature by addressing an empirical question which to-date has been underexplored: the long-run implications on living standards of adult mortality shocks on surviving family members. The study focuses on the Kagera Region in the North-West of Tanzania, an area deeply affected by HIV/AIDS.

Research on the socioeconomic impact of AIDS is wide and varied, and can be partitioned into estimates of macroeconomic costs and analysis of household (microeconomic) impacts. Empirical analysis of the economic impact of high prime-age adult mortality due to HIV/AIDS and other fatal illnesses at the macroeconomic level draws mixed conclusions. Early 2
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Table 2: Direct and spillover effects on property tax payments

||**E**|**arly Paymen**|**ts**|**On-tim**|**e & Late Pa**|**yments**|
|---|---|---|---|---|---|---|
||All|Below<br>Median|Above<br>Median|All|Below<br>Median|Above<br>Median|
||(1)|(2)|(3)|(4)|(5)|(6)|
|**_A. Blocks with 80% treated_**|||||||
|Treated|0.96***|0.86**|1.06**|4.55***|4.12***|5.09***|
||(0.28)|(0.34)|(0.42)|(0.74)|(0.79)|(0.81)|
|Untreated|1.10**|0.55|1.58**|0.79|-1.25|2.56**|
||(0.43)|(0.50)|(0.67)|(1.01)|(1.16)|(1.27)|
|**_B. Blocks with 50% treated_**|||||||
|Treated|1.07***|1.24**|1.02|4.87***|4.81***|5.67***|
||(0.41)|(0.50)|(0.62)|(0.93)|(1.07)|(1.08)|
|Untreated|-0.02|0.10|-0.03|-0.10|1.34|-0.76|
||(0.34)|(0.43)|(0.50)|(0.91)|(1.00)|(1.14)|
|**_C. Blocks with 20% treated_**|||||||
|Treated|0.69*|0.85*|0.52|4.97***|5.41***|4.40***|
||(0.42)|(0.52)|(0.63)|(0.99)|(1.21)|(1.27)|
|Untreated|0.11|0.68**|-0.42|-0.18|0.61|-1.09|
||(0.26)|(0.33)|(0.38)|(0.72)|(0.77)|(0.82)|
|Payment rate of pure control|5.15|3.63|6.49|34.37|23.53|43.91|
|Observations|68,806|32,361|36,445|68,806|32,361|36,445|
|Number of clusters (blocks)|3,981|2,013|1,968|3,981|2,013|1,968|

_Notes_ : This table shows the results from saturated OLS regressions. The dependent variable in columns (1)-(3) is an indicator for paying the October 2020 bill by October 3rd (early payments); while in columns (4)-(6) we use an indicator for paying the October 2020 bill by October 31st (includes early, on time, and overdue payments). Columns (2) and (3) break the main result from column (1) into blocks below and above median compliance in 2019. We define compliance as the share of bills paid by block in 2019 with median value of 0.56 (see Figure B.15). Each column corresponds to a separate regression. The omitted category corresponds to blocks where no accounts were treated (pure control). Panel A shows the results for blocks where 80% were treated, panel B for blocks with 50% treated, and panel C for blocks with 20% treated. The letters were delivered between September 28th and October 7th. The due date for the October 2020 bill was October 9th. The row _Payment rate of pure control_ displays the constant of each regression, corresponding to the average payment rate in blocks with no treated units. Standard errors clustered by blocks are reported in parentheses. * p _<_ 0.10, ** p _<_ 0.05, *** p _<_ 0.01 35
benchmark when the only goal of fiscal policy is to smooth the consumption of hand-to-mouth households. Surprisingly, columns (1) and (2) of Table 2 show that the BBR outperforms the SSR. Moreover, the difference in welfare is significant: the welfare loss is 6% larger under the SSR. This result is in line with Mendes and Pennings (2017), where BBR outperforms SSR in RBC models (which are similar to the flexible price economy here). Still, it is at odds with the literature that finds substantial welfare gains from adopting structural rules over balanced budget rules for commodity exporters.

The OSR is shown in column (3). The 1q-MPS suggests that a 1 dollar increase in commodity revenues should lead to an increase of 54 cents in transfers, which is about halfway in between the BBR and SSR. The 1q-MPS is procyclical because shocks to commodity prices are highly persistent in SSA (6.7 years of half-life) and should be partly spent, according to the PIH. Acyclical rules such as the SSR oversave windfall revenues (and over-spend when commodity prices are low), which means that in the short term, consumption of the hand-to-mouth households underresponds to changes in commodity prices. The optimal prescribes that 2.5% of the sovereign wealth fund (SWF) should be spent each quarter, which is greater than the 1% quarterly interest rate.AA<sup>26</sup> This θθ implies that the _j_ -year MPS increases slowly as _j_ increases (saved revenues are spent at a 10% (4 x 2.5%) annual rate). A related problem is that the SSR leads to an excessively high standard deviation of public and private assets. In the model, the country spread responds to net public assets (SWF). The rate of return on the SWF will decrease as the SWF increases in size, or alternatively, the interest rate increases when the SWF is small. Therefore, a highly volatile SWF under the SSR makes it harder for Ricardian households to smooth consumption by themselves, as the country’s interest rate also becomes very volatile. In practice, the volatility of

> 26 We also assume that = 0.025 for the BBR and SSR. For the BBR that choice is not important, as net public assets does not deviate substantially from steady state. For the SSR, a (locally) higher AA value of will increase welfare, as it makes transfers more procyclical (closer to OSR). θθ

> AA 17 θθ
Hungary, and Cardenas et al. (2003) for Mexico. ECLAC (2000) shows that FDI in the Chilean telecom sector led to the provision of a wider range of products and services in addition to an increase in the number of telephone lines.

Fourth, FDI in services sectors may result in leaking of managerial, marketing, and organizational know-how and best practices (e.g., linked to the environment or to labor codes) from foreign to domestic providers. Miroudout (2006) documents these knowledge spillovers for the banking, telecom, and transport sectors across developing countries.

The four potential effects from FDI in services sectors just described - price reductions, quality improvements, increased variety of services available, and knowledge spillovers - are likely to stimulate productivity growth within the services sector, for both foreign and domestic providers. The fact that MNCs may have acquired the best performing services firms (some privatized since the late 1980s) instead of opening new subsidiaries could reduce the potential for positive effects of FDI on the performance of Chilean services firms. Nevertheless, the evidence suggests that those positive effects materialized for example in the electricity sector which exhibits significant improvements in labor productivity due to FDI during the 1992-2002 period (Pollitt, 2004).

# **3.2 Effects on the Manufacturing Sector**

The crucial hypothesis that we test in this paper is whether the aforementioned FDIinduced improvements in services sectors benefit the productivity growth of downstream manufacturing users. If present, these dynamic benefits could be classified as pecuniary (rent) spillovers which are a by-product of market interactions (Griliches, 1992). Manufacturing plants benefit from pecuniary spillovers if they use services and the services’ quality improvements are (i) not fully appropriated by services providers and/or 8
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- (i) The list of consumption items included in the questionnaires is mostly consistent with major headings in COICOP classification (2 digit), with the sole omission of expenditure on “alcoholic beverages and tobacco” and “recreation and culture”.<sup>20</sup> However, in some cases the list of consumption items in the HNAP 2022 questionnaire includes items at lower levels of aggregation, including some coarse expenditure headings open to interpretation by respondents (for example: personal care, childcare, NFIs...).

- (ii) No information is available to properly account for housing costs. Information on expenditure on rent paid is available for market tenants, which only constitute 10 percent of households, a sample to small and geographically segregated to attempt estimating any model to impute for the value of housing services consumed by owners or other nonmarket tenants.

- (iii) No information is available on consumer durables possessed by the household.

Another important challenge that needs to be addressed to estimate monetary poverty, is to control for spatial price differences. Unfortunately, CBS does not produce any subnational CPI index and lacking detailed information on food and non-food consumption items, it is not possible to estimate one using HNAP survey data. A possible approach is to use a proxy food price index constructed using “standard food basket” price estimates at the governorate level produced by WFP (Table 6). In Syria, WFP standard food basket is set at a group of dry goods providing 2,060 kcal a day for a family of five during a month. The basket includes 37 kg bread, 19 kg rice, 19 kg lentils, 5 kg of sugar, and 7 liters of vegetable oil. WFP provides governorate level estimates on such basket in its monthly “market price watch bulletin”, building on market level price information it has been collecting in the country since 2011.

_Table 6: Spatial price deflator based on WFP Standard Food Basket (SFB)_

||Standard food basketprice(SYP)|Spatialprice deflator|
|---|---|---|
|Damascus|342,867|106.2|
|Aleppo|310,336|96.1|
|Rural Damascus|340,465|105.4|
|Homs|318,922|98.8|
|Hama|334,474|103.6|
|Lattakia|355,953|110.2|
|Idleb|322,260|99.8|
|Al-Hasakeh|253,223|78.4|
|Deir-ez-Zor|273,609|84.7|
|Tartous|346,070|107.2|
|Ar-Raqqa|290,455|90.0|
|Dar’a|352,944|109.3|
|As-Sweida|347,134|107.5|
|Quneitra|341,690|105.8|
|National*|322961.6|100.0|

_Notes_ : National average weighted by population _Source_ : World Bank calculation using April 2022 market price watch bulletin and HNAP population estimates 20 The Classification of individual consumption by purpose, abbreviated as COICOP, is a classification developed by the United Nations Statistics Division to classify and analyze individual consumption expenditures incurred by households, non-profit institutions serving households and general government according to their purpose. The classification is generally used by countries in NA estimations and budget surveys, particularly in relation to CPI weights estimation.
models to examine the determinants and effects of international migration. Previous papers that have estimated such models to study temporary migration include Kirdar (2012), Kleemans (2015), Girsberger (2017), Lessem (2018), G ̈orlach (2020), and Adda, Dustmann, and G ̈orlach (forthcoming). This structural economics literature so far has not examined the role of entrepreneurship and self-employment in migration decisions.<sup>8</sup> Our context of temporary, formal migration that is strictly conditional on an employment contract differs from the contexts of prior work in this literature; nevertheless, this is the norm shared by many other sending countries in South and Southeast Asia. Our paper, therefore, provides new insights on the dynamics of migration of millions of low-skilled workers from similar lowerincome origin countries where migration is highly regulated, and self-employment represents an attractive option over informal wage jobs.

The paper is organized as follows: Section 2 provides the contextual background on temporary labor migration from Bangladesh. Section 3 presents the new dataset and descriptive statistics for our sample. Section 4 introduces a set of stylized facts that inform and motivate the dynamic model laid out in Section 5. Section 6 discusses estimation and identification of this model. Section 7 presents our results. Section 8 concludes.

# **2 Background and Context**

Bangladesh is one of the main countries of origin of low-skilled labor migrants. It ranked fifth worldwide, with an estimated 7.8 million workers working abroad in 2018, the year before our survey was conducted (Ahmed and Bossavie 2021). In relative terms, the incidence of migration among the working-age population is also high. As of 2017, about 13 percent of the total working-age male population of Bangladesh (ages 15-64) was currently or in the past employed overseas. Oil-exporting Gulf Cooperation Council (GCC) member countries are the main destinations for these migrants. More than 750,000 workers have emigrated annually in recent years, and over time the magnitude of migration outflows has risen steadily with the labor demand in the main destination countries. Though long-term trends show that emigration from Bangladesh is rising, there is noticeable year-to-year volatility. Figure 1 shows that these variations are closely tied to fluctuating oil prices. Fuel exports are the single-most important source of income and a major determinant of labor demand in the destination countries of most Bangladeshi migrants. Although emigration correlates with oil prices, wages do not (Figure 1). This indicates that labor demand poses the binding constraint, whereas supply at prevailing wage differences between destinations and Bangladesh – is rather elastic a feature we exploit in our estimation of the model (see Section 5).

> 8See Dustmann and G ̈orlach (2016) for a survey of the structural literature on temporary migration.

7
We consider in the next section trends in employment in agricultural labor, and in agricultural wages, to see to what extent these provide corroborating evidence to the poverty estimates above.

# **III.  Agricultural Employment and Agricultural Wages**

Historically, employment in casual agricultural wage labor has been shown to be strongly correlated with poverty in rural India (Lal, 1976, Singh, 1990, Lanjouw and Stern, 1998, Sharma 2001, Sundaram, 2001, Himanshu, 2004). More recent data suggest that this is still the case. The “odds” of being employed in agricultural wage labor fall monotonically as one rises in the consumption distribution. And there is only slight evidence of this association weakening over time (Table 2). Other dimensions of wellbeing such as education levels and caste status have also been shown to be strongly and inversely correlated with agricultural wage employment (Kijima and Lanjouw, 2005).

Agricultural wage employment continues to employ over 20% of adult males, and has expanded steadily since 1983, until a recent decline between 1999/00 and 2004/05 (Table 3). For women, although far fewer are judged to be economically active, the importance of agricultural labor employment is even more pronounced. There is considerable heterogeneity among states, with several states with higher agricultural employment shares in 2004/5 than, say, in 1987/8 (Appendix Table 1).

This evidence suggests that agricultural wage employment and agricultural wages in particular, can serve as a valuable window on living standards in rural areas. As suggested by Deaton and Drèze (2002), agricultural wages can be viewed not only as useful proxies of poverty but can also be seen as indicators of poverty in their own right insofar that they capture the reservation wages of the rural labor force.

Trends in state-level daily agricultural wages estimated from NSS data suggest much heterogeneity in levels and trends across states. During the 1980s, in 8 states, real wages declined (Table 4).<sup>3</sup> This pattern accords with the widely-held notion that 1987/8

> 3 Agricultural wage data are available in India from a variety of sources. Himanshu (2004) provides a detailed assessment of the different sources available, and argues that calculation of agricultural wages directly from the NSS surveys is not only feasible, but quite possibly yields more reliable figures than are available from alternative sources.  He cautions against the calculation of agricultural wage rates from the 1987/8 NSS round, arguing that the unit record data do not produce wage rates that are readily comparable to wage estimates for that year published by the NSS itself.  We have chosen to calculate and report the

6
**Mexico** - **Technology, Wages, and Employment**

# **TECHNOLOGY AND SKILL DEMAND** IN MEXICO

# **Gladys LUpez-Acevedol**

JEL Codes: L60 ; L20 ; J31 ; J38.

> ' This research was completed as part of the "Mexico - Technology Wages and Employment" study at the World Bank. We are grateful to the INEGI for providing us with the data. Joseph S. Shapiro and Erica Soler provided valuable research and editorial support.
j i(d RFkrmcIi W)ORKING RP.\iAt 2466

# Summary findings

tIsing household survey data for 1998, Datt and Hoogeveen assess the distributional impact of the recent economic crisis in the Philippines. The results suggest that the impact of the crisis was modest, leading to a **5** percent reduction in average living standards and a 9 percent increase in the incidence of poverty-with larger increases indicated for the depth and severity of poverty.

The greater shock came from El Ninio rather than through the labor market. The labor market shock was progressive (reducing inequality) while the El Nifio shock was regressive (increasinig inequality).

Not all households were equally vulnerable to the crisis-induced shocks. Household and community clharacteristics aiffected the impact of the shocks. Ownership of land made households maore susceptible to the El Niflo shocks; higlher levels of educaition made househiolds more vulnerable to wage and employment shocks.

The inpact of the crisis was greater in miore commercially developed communities. Occupational diversity within a household helped mitigate the adverse imipact.

Ther-e is some1w evidenice of consumlption smoothing by the houselholds affected bv the crisis, but the poor were less able to protect theil consumption, which is a matter of policy concern.

This paper-a product of the Poverty Reduction and Economic Management Sector Unit, East Asia and Pacific Regionis part of a larger effort in the region to better understanid the social impact of the crisis. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Taranaki M\4ailei, room MC8-142. telephone 202-458-7347, fax 202-522-1557, email address tmailei@;worldbank.org. Policy Research Working Papers are also posted on the Web at www.worldbaink.or-g/research/workinigpapers. The authors may be contacted at gdatt(/(worldbank.org or hhoogeveen(@.econ.vLi.nl. October 2000. (38 pages)

> _Ihe Policy Research WXorking Paper Series disseminates the findings of zerk in progrress to encounrae the exchange of idleas alo(t deuelopment issues. An objective of the series is to get the fi/nciigs out quickly, even if the preseltationIs ar-e less than fully polished. The papers carry the names of the authors anid shonid be cited accordingly. Thet findi,s, inloepretations, and conclusios expressed inl tbis paper are entirely those of the authors. They do not necessarily represent thz viezv of the W"orld Baik, its Lxecutiz e Directors, or the countries they represenzt._

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