rafmacalaba/data-use-mentions-extended huggingface dataset:
This is because all the poorest receive transfers with universal targeting, while some of them do not with CBT (although those who do receive higher amounts). Finally, PMT is only slightly above universal targeting in terms of poverty-severity reduction – by 0.23 to 0.73 points.<sup>27</sup>

# _Performance in reaching the most food-insecure households_

When considering food insecurity as a well-being metric using measures which are not distributionsensitive, the median PMT and CBT targeting schemes perform similarly to a random allocation of benefits (Table 3). The median CBT and PMT programs provide, respectively, 5% and 2% more resources to the most food insecure households than would a random allocation. There are however notable exceptions in two databases, where both PMT and CBT targeting schemes make a significant difference. These are the two data sets with the lowest CBT selection rates. In Burkina Faso 2, the median CBT and PMT program provide 83% and 38% more resources to the food insecure, respectively. The opposite result is found in Senegal 1, where the CBT and PMT programs provide 13% and 27% more resources to the food insecure, respectively. This opposite result may be a result of several factors, including the scope of geographical targeting and the inequality levels.

Turning to distribution-sensitive measures based on the FCS, the difference between CBT and PMT appears negligeable (Table 5). PMT targeting schemes outperform CBT schemes in all cases but one, according to the simulated reduction in the gap and the severity of food insecurity, but magnitudes are very small. Moreover, in a majority of cases (Chad, Niger 1, Niger 2, Senegal 2), a universal allocation of benefits performs better than alternative targeting schemes based on both the simulated reduction of the gap and the severity of food insecurity. For example, in Niger 2, where the difference is the largest, the FCS severity decrease for PMT is 1.08 versus 1.50 for a universal allocation of benefits.
conducted every four to six years and data collection takes over a year, we allow matching EDD data with up to three years backward or forward relative to the WBES to enhance the size of the final dataset. Table A2 in the Appendix displays the list of countries included in the analysis along with the corresponding time adjustments, if applicable.

Figure 3 presents preliminary evidence of the relationship between uncertainty in the duration of the import process and firms’ export dynamics in developing countries. Once country, destination, sector and year fixed-effects are accounted for, increases in import uncertainty appear to be significantly associated with higher exit rates of exporters and lower probability of entering exporters to survive past the first year of exports, thereby hinting at a potential adverse effect on firms’ exporting status. However, Figure 3 also suggests a positive correlation between import uncertainty and firm entry rates in export markets. Taken together, these scatter plots seem suggestive of export experimentation and failure leading to a substantial turnover rate or churning as firms enter and exit export markets, yielding low survival rates (Brenton, Saborowski, and von Uexkull, 2010; Brenton, Cadot, and Pierola, 2012). We hypothesize that such dynamics are driven by uncertainty in the time to import. Specifically, we conjecture that unpredictability in border clearance times for key inputs disrupts the production process, making the importing exporter likely to miss delivery deadlines. If such incident happens frequently, exporting firms risk losing their credibility as reliable suppliers, and time-sensitive buyers may decide to terminate

> 21We thank Ana Margarida Fernandes and Hibret Belete Maemir for kindly computing the EDD statistics at the countrydestination-sector-year level.

10
**Table 6: Baseline Gravity Model Estimation with Aggregate Labor Clause Indicator**

|VARIABLES|(1)<br>OLS<br>RE|(2)<br>OLS<br>FE|(3)<br>PPML<br>Full FE|(4)<br>PPML Any<br>Labor Clause|
|---|---|---|---|---|
|Regional Trade Agreement Indicator|0.356***|0.165***|0.0965**|0.164***|
||(0.0222)|(0.0246)|(0.0397)|(0.0493)|
|Any Labor Clause Indicator|-0.209***|-0.206***||-0.193***|
||(0.0301)|(0.0325)||(0.0524)|
|GDP Importer|0.882***|0.767***|||
||(0.00600)|(0.0165)|||
|GDP Exporter|1.043***|0.525***|||
||(0.00642)|(0.0191)|||
|1 = Contiguity|1.348***<br>(0.0927)||||
|Origin GATT membership|0.563***<br>(0.0299)||||
|Destination GATT membership|0.192***<br>(0.0283)||||
|1 = Common official or primary language|0.779***<br>(0.0376)||||
|1 = Common colonizer post 1945|0.368***
# **2.5 Comparison of Additional Human Capital across Interventions**

Table 2 compares the additional human capital available under the four different treatments, which the entrepreneur can use to help build skills in her firm (either personally or organizationally): (i) business trainer; (ii) business consultant; (iii) insourced worker; and (iv) outsourced professional. This comparison uses data collected from a monitoring survey of the insourcing and outsourcing treatments, and from requests for details from the training agency (EDC) and the consulting advisory company (Growbridge). An important caveat is that these comparisons measure formal schooling, experience and certified skills, but do not capture any possible advantage that younger specialists may have in using new digital marketing tools such as social media.

The four treatments differ considerably in the skill level of the additional human capital and the intensity with which the intervention provided it. The common approach of training the entrepreneur lies at one extreme (higher experience; lower intensity). The business trainers all have some form of skill certification, average over 15 years of work experience, and have an average age of 49 years. 82% have post-graduate education, and they are paid just over 1 million Naira (US$2,960) per month. However, the trainers do not work directly in the firms – instead, firms only receive 12 days (84 hours) of their time in a group classroom setting.

At the other extreme lies insourcing (lower experience; higher intensity). The insourced workers hired by firms are much younger (average age 29 years), with 3.5 years of work experience on average. And only 24% of these workers have a formal skill certification, while just 32% have post-graduate education. Firms paid these employees 50,000 Naira (US$136) per month on average, but had them working inside the firm for an average of 42 hours per week (1,455 hours in total if they stayed on for
state, sector (census versus sample) and industry, a joint return can be furnished. In the population of firms, fewer than 2% of the observations report more than one factory, and we will use the term The key variables we construct from the ASI data are output, material input, labor, and capital.<sup>4</sup> We drop closed firms from the dataset, and we include only firms with positive values of the key variables. To address a few extreme outliers, we also trim the top 0.5% of output and material input values.

We deflate output using industry-specific wholesale price indices (WPI) from the Government of India’s Handbook of Industrial Statistics. Similarly, our material input measures are deflated by constructing deflators using the WPI along with India’s 1993-94 Input-Output Transactions Table. Labor is measured as the total number of people employed by the firm, and capital is measured by deflating the book value of capital by the WPI for machinery.<sup>5</sup> Summary statistics for the population are presented in Table 3. Only open firms that have positive values of our key variables are included. Sampling weights are applied to the summary statistics in the first column, so the results are representative of the overall organized sector. The second column shows results for the firms that were sampled, without applying sampling weights. Since larger firms are surveyed more often than smaller firms, the mean and median values of output, capital, material inputs, and labor are much larger in the sampled population rather than the estimated population.

# **3.2 Creating a Panel**

The ASI data provide unique firm identifiers beginning in 1998. However, it has not previously been possible to track firms prior to 1998, and thus to follow them during the most significant period of reforms. We overcome this challenge by matching individual firms from one year of

> 4Output includes the ex-factory value of products, the increase in the stock of semi-finished
. At the macro level, China has experienced rapid economic growth over the past decades, with its GDP per capita increasing by around six-fold over our sample period (China Statistical Yearbook, 2014). At the micro level, both private firms and private entrepreneurs have emerged in multitudes during the reform era. The growth rate of the private sector has far outpaced that of the public sector, making it a defining feature of China's growth patterns (Song et al., 2011).

In our study, we shed light on the dynamics of the BE and entrepreneurship in China’s private sector by providing the most ambitious and comprehensive descriptive analysis over

> 5 Data sources: Penn World Table version 9.0. The share of GDP is based on output-side real GDP at chained PPPs (in mil. 2011US$).

3
# **Appendix**

# **Estimating mortality: A comparison between the sample based approach and the reconstruction approach**

This paper uses the sample based approach to estimate the impact of the mortality from the Khmer Rouge period on the current Cambodian population structure. To the best of my knowledge, it is the first to do so with a nationally representative sample of women interviewed about the birth, survival and deaths of all their siblings. However, this sample, interviewed more than 20 years after the mortality crisis is by definition a sample of survivors and, as such, as already explained in section II, likely to substantially underestimate mortality, since families in which all siblings died will not be included in the counts and, similarly, families which experienced a large proportion of casualties are less likely to be included in the sample. Families with a large migration rate are also less likely to be counted.

This appendix attempts to quantify the degree of underestimation of the mortality crisis by comparing death counts obtained using the death probabilities calculated from our sample of survivors with excess mortality estimates obtained using the reconstruction method. The most careful reconstruction exercise has been realized by Heuveline (1998 (a), 1998 (b), 2001 (a), 2001 (b)). He estimated, as baseline, the 1970 population of Cambodia by projecting the data from the 1962 census. He estimated the 1980 population by projecting backward data from 1993 electoral lists. Using “normal” mortality parameters and estimates of migratory flows, he then projected forward his 1970 estimate into 1980 and backward his 1980 estimate back to 1970. From both projections, the residual between the projection under “normal” parameters and the actual estimate can be computed. The average of the forward and the backward projection residuals is then presented as the number of excess deaths.

The results of the comparison are presented in table A1. For six birth cohorts born between 1940 and 1969 for which the sample based approach could provide reliable estimates of the death probabilities
|62.8|32.8|42.7|13.9|
|Percent of carriers passing<br>IATA/IOSA audit|100|33|0|33.3|0|0|
|FAA/IASA audit status|No Audit|No Audit|No Audit|Passed|Failed|No audit|

_Source:_ Bofinger 2009. Derived from AICD national database (www.infrastructureafrica.org/aicd/tools/data). _Note:_ All data as of 2007 are based on estimations and computations of scheduled advertised seats, as published by the Diio SRS Analyzer. This captures 98 percent of worldwide traffic, but a percentage of African traffic is not captured by the data. The Herfindhal-Hirschmann Index (HHI) is a commonly accepted measure of market concentration. It is calculated by squaring the market share of each firm competing in the market and then summing the resulting numbers. A HHI of 100 indicates the market is a monopoly; the lower the HHI, the more diluted the market power exerted by one company/agent. FAA = U.S. Federal Aviation Administration; IASA = International Aviation Safety Assessment; IATA = International Air Transport <u>Association; IOSA = IATA International Safety Audit.</u> The number of city pairs served by airlines in Mozambique, both domestically and internationally, increased between 2001 and 2007, against the declining African trend. The greatest increase was reported in international city pairs, which increased from 10 in 2001 to 31 in 2007. Domestic city pairs rose from 22 to 30 over the same period (figure 7b).

In terms of airport facilities, nontraditional financiers are increasingly playing a role. The construction of a new terminal building in Maputo has been recently finalized, involving Chinese investment of around $75 million, as well as the expansion of an existing military airport in Nacala into a commercial airport, financed by Brazil.

# **Challenges**

Despite the growth in the sector, Mozambique’s
describe the methodology used to administer the diary approach in parallel to the 2005/06 National Household survey and the potential biases it was expected to reduce.

# **2.1 The challenge of collecting reliable information on continuously harvested crops**

Data on agricultural production can be obtained through a range of different instruments and the key issue confronting statisticians and researchers is how to do so at an acceptable trade-off between cost and potential measurement errors. Crop cutting, whereby enumerators actually harvest and physically weigh output from sample plots, is generally considered to be the most reliable and precise way of measuring agricultural output, has two disadvantages. First, the need for continued field presence by a skilled staff increases costs to a point where broad application of this method may become unaffordable. Tightening budgetary constraints faced by relevant line agencies do indeed often result in poorly administered crop 3
countries as destinations. These four countries host 18 of the top 20 and 69 of the top 100 universities globally, as ranked by Academic Ranking of World Universities (the 2016 rankings are available at http://www.shanghairanking.com/ARWU2016.html).<sup>8</sup> Moreover, schooling can provide an important entry point into desired labor markets for talented individuals (Rosenzweig 2006; Grogger and Hanson 2013). Kato and Sparber (2013) show how declines in the availability of high‐skilled visas made American universities less attractive to foreign students, in terms of the number of foreign applicants and also the quality of those applicants as measured by SAT scores, compared to a handful of sending countries that were not impacted by the policy shift. Similarly, foreign students, mostly from East and South Asian countries, make up almost a quarter of the student population in Australian universities and easier entry into the Australian labor market is often cited as one of the key factors in their location choices. At later points in the educational process, Bound et al. (2015b) describe the use of graduate education in US universities to obtain access to the US labor market, and also the buffer that additional education can provide until a labor market match is realized.<sup>9</sup> Even when a labor market match occurs for skilled migrants, there is a substantial possibility of return migration—although the rate seems to vary across skill sub‐groups. The data on the subject remain limited with OECD (2008) representing an extensive effort to compile the currently available information. This report shows that 20‐50 percent of immigrants leave within five years of arriving, depending on the corridor and the time period. These levels are consistent with historical patterns; for example, Bandiera et al. (2013) find that over half of the migrants

> 8 Interestingly, different types of graduate education display varying geographic concentrations. A recent _Financial Times_ ranking of business schools included institutions
from the World Input-Output Database.

Because institutional features of the multilateral trading system constrain policy, we are careful to incorporate them into our empirical strategy. While governments have discretion to offer preferential tariffs bilaterally via various trade preference programs (under the GATT’s Article XXIV or Enabling Clause), they are subject to several relevant constraints. The first is the most-favored-nation (MFN) rule under the GATT, which caps bilateral tariffs for many trading partners at levels below the unilaterally optimal tariff. The implication is that we can observe bilateral optimal tariffs up to, but not above, the MFN threshold. We use non-linear methods to address this partial non-observability, or censoring, problem in the estimation. A second constraint is that some bilateral tariffs are set via reciprocal trade agreements. As

> 2Our study is in the tradition of earlier work examining unconstrained dimensions of policy, including Trefler (1993), Goldberg and Maggi (1999), Gawande and Krishna (2003), Broda, Lim ̃ao and Weinstein (2008), Bown and Crowley (2013), and Blanchard and Matschke (2015), among others.

3
attitudes and values. We merged the information coming from the two respondents in the household. This implies we assume the answer given by the household head is representative of the household opinion.

**Personal and household characteristics used for the estimations are constructed based on the data available in the employment and household characteristics sections.** We used this information to obtain the age, education, ethnicity, religion, and employment status of the respondent. Also, we used this section for the education of the father. We used the household characteristics to construct the location (urban/rural), household size, consumption and assets owned, and the shares of children and seniors. We also extracted information about the education of the father, as an indicator of condition that cannot be affected by the individual, to test whether they play a role in the perceptions of mobility.

**Attitudes and beliefs are obtained from the module of opinions included in the survey, which covered perceptions about the dynamics of the society and valuation of institutions.** For the variable on trust in public institutions, we constructed an index based on trust in five public institutions (Presidency, Cabinet of Ministers, Parliament, Judges and Police). For each institution, the original variables were coded in 5 categories, ranging from distrust to full trust. We collapse this information in three categories and construct an index that can take three values (-1, 0, or 1) corresponding to distrust, neutral or trust in each institution. The aggregate index is the arithmetic average. For fairness, we used a question on what the respondent beliefs is rewarded in society, either effort and intelligence, or contacts and corruption/criminal ties. For market economy support, we took a question asking to express a preference between a market economy or a centrally planned one. Finally,

> 4 It included Mongolia, EBRD country of operation since 2006, and part of the World Bank East Asia and Pacific Region. Turkey is not an EBRD country of
- Kim, Jinyoung, Sangjoon John Lee & Gerald R. Marschke (2009). “International Knowledge Flows: Evidence from an Inventor-Firm Matched Data Set”. In Richard B. Freeman & Daniel Goroff (editors), _Science and Engineering Careers in the United States: An Analysis of Markets and Employment_ , pp. 321–348. Chicago, IL: University of Chicago Press and NBER

- Knack, Stephen & Philip E. Keefer (1997). “Does Social Capital Have an Economic Payoff? A Cross-Country Investigation”. _Quarterly Journal of Economics_ 112(4) (November): 1251–1288

- Krugman, Paul R. (1979). “Increasing Returns, Monopolistic Competition, and International Trade”. _Journal of International Economics_ 9(4) (November): 469–479

- Larra ́ın, Felipe B., Luis F. L ́opez-Calva & Andr ́es Rodr ́ıguez-Clare (2001). “Intel: A Case Study of Foreign Direct Investment in Central America”. In Felipe B. Larra ́ın (editor), _Economic Development in Central America: Growth and Internationalization_ , volume 1 of _Harvard Studies in International Development_ . Cambridge, MA: Harvard University Press

- Maddison, Angus (2003). _The World Economy: Historical Statistics_ . Paris, France: Organisation for Economic Co-operation and Development

- Mankiw, N. Gregory, David Romer & David N. Weil (1992). “A Contribution to the Empirics of Economic Growth”. _Quarterly Journal of Economics_ 107(2) (May): 407–437

- Mansfield, Edward D. (1993). “Concentration, Polarity, and the Distribution of Power”. _International Studies Quarterly_ 37(1) (March): 105–128

- Markusen, James R. (2004). _Multinational Firms and the Theory of International Trade_ . Cambridge, MA: MIT Press

- McCraw, Thomas K. (2010). “Immigrant Entrepreneurs in U.S. Financial History, 1775
- Gibson, J. and McKenzie, D. (2011). Eight questions about brain drain. _Journal of Economic Perspectives_ , 25(3):107–128.

- Gibson, J., Olivia, S., Boe-Gibson, G., and Li, C. (2021). Which night lights data should we use in economics, and where? _Journal of Development Economics_ , 149:102602.

- Giuliano, P. and Ruiz-Arranz, M. (2009). Remittances, financial development, and growth. _Journal of Development Economics_ , 90(1):144–152.

- Global Forest Watch (2023). Annual tree cover loss 2001–2021.

- Global Sanctions Database (2023). The global sanctions database (gsdb) 2023.

- Godlonton, S. and Theoharides, C. (2025). Diffusion of reproductive health behavior through international migration: Effects on origin-country fertility. _American Economic Review_ , 115(10):3597–3637.

- Gonz ́alez, F., Mart ́ınez, L. R., Mu ̃noz, P., and Prem, M. (2023). Higher education and mortality: Legacies of an authoritarian college contraction. _Journal of the European Economic Association_ , page jvad066.

- Goodman, G. L. and Hiskey, J. T. (2008). Exit without leaving: Political disengagement in high migration municipalities in Mexico. _Comparative Politics_ , 40(2):169–188.

- Grossmann, J., Jurajda, , and Roesel, F. (2024). Forced migration, staying minorities, and new societies: Evidence from postwar Czechoslovakia. _American Journal of Political Science_ , 68(2):751–766.

- Guerrero, N. P. and Sviatschi, M. M. (2025). Mass migration and the expansion of criminal networks. Working Paper.

- Hanson, G. H., Kerr, W. R., and Turner