rafmacalaba/data-use-mentions-extended huggingface dataset:
percent of the mean value of _Time_ . In terms of the frequency, about 36 percent of the countries witnessed a change in the value of _Time_ in any two consecutive years on average. Further, over the entire time span of 2006-2010, every country in the sample experienced a change at least once in the value of _Time_ .

# 2.2 _Main explanatory variables_

Our first explanatory variable is the (log of) number of documents required to export and import as measured by the World Bank’s Doing Business project ( _Documents_ ). As mentioned above, to avoid simultaneity problem, we use one year lagged values of the variable. Hence, the regression results discussed below cover the period 2006 to 2010. The mean value of _Documents_ equals 2.73 and the standard deviation is .27. Averaging over time for each country, the highest value of _Documents_ is observed in Central African Republic (3.23) and lowest in Panama (1.96). Computing annual changes in the value of _Documents,_ the mean value of the change equals -.024 or .89 percent of the mean value of _Documents_ and the standard deviation equals .12. On average, in any two consecutive years, over 13 percent of the countries in the sample witnessed a change in the value of _Documents_ . Further, every country in our sample witnessed a change in the value of _Documents_ at least once over the time period under study.

To see how the correlation between _Time_ and _Documents_ varies by income and country size, we interact _Documents_ with a measure of per capita income level and country size. For income level, we use log of GDP per capita, PPP adjusted and at constant 2005 international dollars. Values of GDP per capita used in the paper are average values taken over 2001-2005 ( _Income_ ). The data source for the variable is World Development Indicators, World Bank. We note that lagged values of GDP per capita are used in order to avoid the potential simultaneity 6
|**Table 2: Correlates of Baseline Capital St**|**ock**<br>(1)|(2)|(3)|
|---|---|---|---|
|Hyperbolic Discounter|‐196.1**<br>(82.13)|||
|Low Discount Rate|94.53<br>(73.46)|||
|Lack of self‐control index||‐60.34*<br>(32.48)||
|Feels pressure to share in household|||‐201.3**<br>(87.38)|
|Digitspan Recall|34.02*|35.51*|44.34**|
||(18.24)|(18.32)|(18.10)|
|Raven test score|13.20|15.85|21.77|
||(13.49)|(13.51)|(13.32)|
|Education Years|13.95|13.42|6.674|
||(11.15)|(11.19)|(11.09)|
|Female|‐193.9**|‐198.5***|‐137.8*|
||(75.45)|(75.87)|(75.17)|
|Age|13.63***|14.02***|12.57***|
||(4.162)|(4.179)|(4.228)|
|Father's schooling|1.880|2.144|0.168|
||(7.408)|(7.445)|(7.283)|
|Mother's schooling
# _Market-level data_

Maize price effects are estimated using price data from the Agricultural Market Information System (SIMA), which is run by the Ministry of Agriculture of Mozambique. The database tracks weekly retail prices for a range of core agricultural products (particularly maize, cassava, rice and beans) in 25 markets in cities and towns spread across all provinces in Mozambique.

# _Weather data_

Determining historical weather distributions as well as the timing, intensity and spatial location of anomalies requires long time series and spatially disaggregated data on weather observations. We first listed all weather-related natural disasters that took place in Mozambique within the time frame determined by the dates of the household surveys (IOFs) using the disaster profile information publicly available in the International Disaster Database (EM-DAT 2018). In addition to providing information on the timing, geographical coverage, and human impact of the disasters, the EM-DAT database provides estimates of their economic damages.<sup>2</sup> In a second stage, we initially cross the long list of floods with daily precipitation data recorded by the Tropical Rainfall Measurement Mission (TRMM) in the Multi-Satellite Precipitation Analysis (TMPA) for the period 2000 to 2012. These data have a resolution of 0.25 by 0.25 degrees, which in Mozambique corresponds to grids of approximately 25 by 25 kilometers (Huffman et al. 2007). In contrast to other high-resolution precipitation data sets such as CHIRPS and CRUTS, which combine remote sensing data with readings from weather, TMPA contains rainfall data based only from satellite records, ensuring consistency in the measurement methodology.

To obtain quantitative measures on the intensity and location of cyclones, we use daily wind speed data from the U.S. National Oceanic and Atmospheric Administration (NOAA) and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). This database stores wind speed records for the period 1950-2017 for grids with resolution of 0.25 by 0.25 degrees The GFS is a global weather forecast model that contains data on dozens
**6**

contract enforcement, and accounting practices will boost financial intermediary development and induce a rapid acceleration in economic growth.

> This paper complements recent microeconomic efforts aimed at reconciling whether financial development is simply a good predictor of economic growth. Rajan and Zingales **(1998)** show that, in countries with well-developed financial systems, industries that are naturally heavy users of external

> finance grow relatively faster than other industries. Alternatively, in countries with poorly developed

> financial systems, industries that are naturally heavy users of external finance grow more slowly than other industries. Using firm-level data, Demirgu9-Kunt and Maksimovic **(1996)** show that firms in countries with better developed financial systems grow faster than they could have grown without this access. While these microeconomic studies must respectively identify (a) the "natural" tendency of industries to use external funding and **(b)** how fast firms would have grown in different financial

> environments, the results support the conclusion that better financial systems facilitate economic development.<sup>3</sup>

The rest of the paper is organized as follows. Section II presents the results on causality, using purely cross-sectional data, while Section HI discusses and presents the differenced and system dynamic panel results. Section IV provides information on how the legal and accounting environment explain cross-country differences in financial development. Section V concludes.

> **3** Furthermore, this paper complements an innovative event study **by** Jayaratne and Strahan **(1996). They** show that when individual states of the United States relaxed intrastate branching restrictions the quality of bank loans rose and per capita **GDP** growth accelerated.
bank lending) by non-residents net of their own disinvestment in the reporting economy.<sup>8</sup> Similarly, gross private outflows refer to flows by residents, net of their own disinvestment. We use quarterly net capital inflows as our main measure. Quarterly gross capital inflows are used to check the robustness of our results to the alternative definition of

> 6 The absolute ratings and relative ratings have the same cardinal measure but there is no strict correspondence in terms of the values.

> 7 The data collection exercise for capital flows addresses two challenges: 1) Consistency of definitions for specific categories of flows (for instance, there are differences in definitions and, therefore, values between the various sub-components of portfolio flows and debt reported by World Bank World Development Indicators, Global Economic Prospects and the IMF Balance of Payment statistics); 2) Issues due to change in Balance of Payments statistics guidelines. Historical capital flows data currently available from the IMF Balance of Payments statistics (on which the World Bank World Development Indicators data are largely based) are currently inconsistent between the pre-2005 and post-2005 periods, given the transition from BPM5 to BPM6 definitions.

> 8 These are standard components used to aggregate capital flows in the literature (see Ahmed and Zlate, 2014).

11
‐Sector‐year|no|yes|no|no|yes|no|
|Firm FE|no|no|yes|no|no|yes|
|Firm controls|yes|yes|yes|yes|yes|yes|
|Observations|140,594|140,569|121,559|140,594|140,569|121,559|
|R‐squared|0.224|0.225|0.286|0.178|0.182|0.290|

Note: The reported coefficients are beta coefficients, t‐values in parentheses. The explanatory variables are measured at time t, while the dependent variables are 3‐year changes between t and t+3. The explanatory variables show the share of HGFs in different industries at the same microregion and county, by using the 2‐digit input‐out matrix from OECD STAN. Firm controls are log employment, labor productivity and log capital per labor ratio. Standard errors are clustered at the county‐industry (2‐digit NACE)‐year level. The definition of HGF is the 3‐year Birch employment definition. Small firms are firms with less than 5 employees A relevant concern about our empirical specification is that the share of HGFs can also be correlated with other industry characteristics. For example, the share of HGFs in an industry may be strongly correlated with the share of foreign firms. If foreign firms generate productivity spillovers, it is possible 18
**Figure 1b: SAARC Trade vs. Other Regions**

<!-- Start of picture text --> 80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>ASEAN SAARC NAFTA EU<br>Intraregional trdae(%)<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010<br><!-- End of picture text --> _Source_ : Calculations based on Direction of Trade Statistics Online Database (DOTS), IMF.

**Figure 2: Bangladesh Trade with India (1980–2010)**

<!-- Start of picture text --> 4500<br>4000<br>Imports from India<br>3500<br>3000<br>2500<br>2000<br>1500<br>1000<br>Exports to India<br>500<br>0<br>US$ million<br>1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010<br><!-- End of picture text --> _Source_ : IMF DOTS.

Bangladesh‘s trade with neighboring countries is unequally distributed, having little to do with Bhutan, Nepal, or Sri Lanka. India is Bangladesh‘s primary trading partner, followed by Pakistan. Bangladesh has a high deficit in its trade with India––having risen from US$ 44 million to US$ 2.5 billion from 19812009 (Figure 2).<sup>17</sup> The ten years from 2000-2009 have seen the fastest rise in Bangladesh‘s exports to India (42.65 percent per annum growth), while Bangladesh‘s import growth from India declined to 16.24 percent per annum (Figure 3). Nevertheless, Bangladesh exports are only 1 percent of India‘
job postings reduce information costs and unemployment rates and improve job match quality in developed countries (Beard et al., 2012; Kuhn and Mansour, 2014; Mang, 2012). Third, online job portal data, particularly the data from Rozee.pk, are relevant to specific challenges in Pakistani labor markets. The youth, especially well-educated young people, suffer a higher unemployment rate, and wage employment needs to increase. The country faces a gender disparity in labor force participation (LFP).<sup>8</sup> The data from Rozee.pk are suitable to analyze these challenges because the online job portal is mostly used by well-educated young people for wage jobs, and many job postings are gender earmarked.

# 2. Online job portal data from Rozee.pk

Rozee.pk, founded in 2007, is a leading online job portal in Pakistan. This paper analyzes a data set consisting of 5.0 million jobseekers and 108,000 registered employers corresponding to 412,000 jobs posted on the platform. The data provided by Rozee.pk to the study team consist of four types of data sets: jobseekers, employers, job postings, and transactions.<sup>9</sup> The data set of jobseekers is based on their resumes created at Rozee.pk and includes rich information about demography, education, professional experience, skills possessed, and current and desired salaries. The employer data set is based on employers’ profiles at Rozee.pk. The job posting data set is an archive of all job postings and has virtually all information included in job postings, such as job titles, job descriptions, qualifications, and salary ranges. The transaction data set is a record of all applications as to who applied for which job postings on what date and time, and whose applications were viewed by employers. Information about application results, such as who was shortlisted, is also available, although this information is incomplete since application results are voluntarily updated by employers. This paper
- Defrance, D., E. Delesalle, and F. Gubert. 2020. “Is Migration Drought-induced in Mali? An Empirical Analysis Using Panel Data on Malian Localities Over the 1987-2009 Period.” _Institut de recherche économiques et sociales, UC Louvain Discussion Paper_ .

- Dell, M., B. F. Jones, and B. A. Olken. 2014. "What do we learn from the weather? The new climate-economy literature." _Journal of Economic Literature_ 52.3: 740-98.

- Dessy, S., F. Marchetta, R. Pongou, and L. Tiberti. 2020. “Climate Shocks and Teenage Fertility.” _GLO Discussion Paper 490_ .

- Dessy, S., L. Tiberti, and D. Zoundi. 2023. “The gender education gap in developing countries: Roles of income shocks and culture.” _Journal of Comparative Economics_ 51(1): 160-180.

- Dessy, S., L. Tiberti, M. Tiberti, and D. Zoundi. 2021. “Polygyny and Farm Households' Resilience to Climate Shocks.” _World Bank Policy Research Working Paper_ 9663. Washington, DC: World Bank.

- Deuchert, E., and C. Felfe. 2015. “The tempest: Short-and long-term consequences of a natural disaster for children’s development.” _European Economic Review_ 80: 280-294.

- Diakakis, M., et al. 2015. "Hurricane Sandy mortality in the Caribbean and continental North America." _Disaster Prevention and Management_ 24(1): 132-148.

- Díaz, J.J. and V. Saldarriaga. 2020. “A Drop of Love? Rainfall Shocks and Spousal Abuse: Evidence from Rural Peru”  http://dx.doi.org/10.2139/ssrn.3662976

- Dillon, A., and E. Quinones. 2010. "Gender-differentiated asset dynamics in Northern Nigeria: Background paper prepared for the state of food and agriculture 2010–11." _ESA Working Paper_
**Figure 3:  Destination of manufacturing output**

<!-- Start of picture text --> Share of output sold domestically Share of output exported<br>0.80 0.08<br>0.70 0.07<br>0.60 0.06<br>0.50 0.05<br>0.40 0.04<br>0.30 0.03<br>0.20 0.02<br>0.10 0.01<br>0.00 0.00<br>1995 2005 2015 1995 2005 2015<br>Intermediates Final demand Intermediates Final demand<br>SSA average SSA average SSA average SSA average<br><!-- End of picture text --> Notes: Own calculations based on the EORA data.

In sum, the economy of Rwanda is even less well integrated with international markets than most sub-Saharan African countries. On the output side, manufacturing firms export only 2% of output, compared to 11% for the rest of the region. More of its agricultural output is exported, but at 6.8% that fraction is still much lower than the 25.4% that is the average for the region. On the input side, the difference is smaller: 13.3% of inputs in manufacturing are imported, which is similar to the 14.5% average for the region. Inputs to agriculture are almost all sourced domestically, but the same pattern prevails in the rest of the region.

The objective in the remainder of the paper is to investiage what this aggregate exposure implies at the firm level. How many firms are internationally engaged, which firms, and to what extent? Of the firms selling or sourcing internationally, what regions are they mostly exposed to and what products are they producing? To answer these questions, we work with an exhaustive dataset of all formally registered firms in Rwanda that is introduced in the next section
percent of installed power generation capacity, making the country vulnerable to droughts. Droughts in 2015/2016 and 2019 led to blackouts and power rationing (UNCTAD 2022). Financial challenges at the state-owned electricity utility, a weak coordinating environment, and limited private sector participation further contribute to electricity issues in Zambia (UNECA 2021, UNCTAD 2022).

## 6.4. Regulatory environment and confluence with informality

Formal firms in Zambia compete heavily with informal firms, reflecting difficulties in accessing highervalue markets and amplifying distortions from excessive formal regulatory and tax burdens. Informal firms may hinder the scale-up of formal competitors if their informal status provides them with cost or operational advantages (e.g., lower regulatory or tax burdens), creating an uneven playing field (Amin, Ohnsorge and Okou 2019). Since informal firms are not covered in this analysis, their impact on productivity can be observed as productivity declines among formal firms that experience sales or margin declines, rather than as cross-firm reallocation of resources. According to the 2019 Enterprise Survey, nearly 65 percent of firms compete with informal firms—higher than many peer countries— (Figure 43) and informal sector practices are the third-most cited business environment obstacle. These competitive distortions result from informal competition coinciding with burdensome requirements for formal firms. Senior managers of formal firms in Zambia report spending 8 percent of their time dealing with regulatory requirements, higher than the averages for SSA and aspirational peers (Figure 44). Competition with the informal sector may also reflect weak market access, forcing formal firms to compete with informal firms for a limited pool of local customers.

<!-- Start of picture text --> Figure 43. Firms competing with informal firms Figure 44. Senior management time spent on<br>(Percent of latest Enterprise Survey respondents) regulatory requirements (Average of latest<br>Enterprise Survey respondents)<br>80% 14%<br>70% 12%<br>60% 10%<br>50% 8%<
Policy Research Working Paper 10991

# **Abstract**

This study documents short-term economic mobility in Malaysia over the first two decades of the twenty-first century, at the population level and for various subgroups. The findings show broad and steady improvements in well-being, as evidenced by large decreases in chronic poverty and significant increases in persistent economic security. The study employs a synthetic panel approach based on nationally representative micro-level data for 2004–22, with a refinement that allows presenting bootstrap point estimates and standard deviations. In addition, the study investigates several poverty and vulnerability scenarios, as well as relative mobility. First, the results indicate that chronic poverty has decreased to 2–3 percent of the population. Nevertheless, progress is not uniform: around 15 percent of the population in rural East Malaysia lives in chronic poverty. Second, the study finds considerable increases in sustained economic security—the extent of improvement, however, depends on the approach and income thresholds that are used to define security. Moreover, ethnic and regional differences in secure status are sizable at higher income class thresholds. The largest differences are of a regional dimension: an individual in urban Peninsular Malaysia is more than three times more likely to live in economic security than someone in rural East Malaysia. Altogether, the study observes upward movement across the board but little evidence of dramatic changes in the relative positions of societal groups.

This paper is a product of the Poverty Global Department. 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://www.worldbank.org/prwp. The authors may be contacted at a.g.m.j.rongen@vu.nl.

_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
# Figure II: Share of Family Firms Across Countries

<!-- Start of picture text --> (a) GDP (b) Rule of Law<br>.6 BIHBGR<br>BIH BGR .5<br>RUS<br>.5<br>RUS<br>.4<br>ITA<br>.4 SRB SVN EST<br>SRB EST SVN ITA .3 CZE ESPPRT<br>.3 CZE ESP .2 CHE<br>PRT POLLVALTU DEU NLD<br>.2 POLLVALTU DEUNLD CHE .1 UKR FRA<br>FRA<br>.1 UKR 0<br>8 9 10 11 12 −1 0 1 2<br>Log 2011 GDP pc Rule of Law Index<br>Data shows share of FOFM firms in each country against 2011 GDP. Data shows share of FOFM firms in each country against RoL index.<br>(c) Trust (WVS) (d) Enforcing Contracts Rank (WB DBS)<br>.6 .6<br>BIH BGR BGR BIH<br>.5 .5<br>RUS RUS<br>.4 .4<br>ITA ITA<br>SVN SVN<br>EST SRB EST SRB<br>.3 ESP CZE .3 ESP CZE<br>PRT<br>.2 CHE .2 CHE<br>LTU POL LVA DEU NLD DEU LTULVA NLD POL<br>FRA FRA<br>.1 UKR .1 UKR<br>0.2 0.3 0.4 0.5 0.6 0 50 100 150<br>Trust Enforcing Contracts Rank<br>Data shows share of FOFM firms in each country against WVS trust score. Data shows share of FOFM firms in each country against enf contracts rank from WB DBS.<br>Figure III: Trust as a Proxy for Rule of Law and Enforcing Contracts<br>(a)
388|
|_ln FVA_|14,943|6.94|2.079|
|_ln VA_|15,089|8.76|2.23|
|_ln VA_GVC_|15,087|6.83|2.305|
|_ln V_D_|14,944|8.04|2.846|
|_VD_share_|15,089|0.60|0.424|

**Notes** : Asian Development Bank estimates based on Wang, Wei, Yu and Zhu (2017) using Asian Development Bank Multi-Regional Input Output Tables (2011 - 2017) and Financial Times fDi Markets Database.

# 5 Direct FDI Effects and GVC Participation

## 5.1 Empirical strategy

To identify the direct effects of FDI on the labor productivity of a country-sector, we specify the regression equation as follows:
unbanked to be households without access to savings accounts, the ACIM survey suggests that the unbanked in urban Colombia reach close to 70%. A similar survey by the same company, in Mexico, reported findings of unbanked households at 85%.

4. The DANE survey, applied to a representative sample of 1,600 Bogotá households in 2002, was sponsored by the World Bank, but designed and implemented by the Center for Economic and Development Studies in the University of Los Andes (CEDE) in conjunction with the National Administrative Statistics Department (DANE)’s program of Household Surveys (ECH).

5. In this study the term ‘banked’ refers to households and to individuals who maintain deposits (savings, checking or CDT account) in some formal sector financial institutions, including commercial and social interest banks, regulated cooperatives and credit unions (these last 45
components are zero. The LM is distributed as chi-squared with one degree of freedom. If the null is rejected, the random effect model is more appropriate.

# **3. Analytical approach**

## **3.1 Data and definition of indicators**

## **_Our data set is based on a panel of 22 countries for a period beginning in 1989 and extending through 2009._**

The outcomes used for our econometric as well as our case study analysis are the four indicators of power sector performance listed in Table 1 that are used to measure the determinants of power sector performance, namely residential access to electricity, energy sold per employee of electricity suppliers as an indicator of labor productivity, average electricity tariff level as an indicator of financial efficiency, and the index of carbon dioxide emissions as an indicator of environmental sustainability.

**Table 1 Selected Power Sector Performance Indicators**

|**Variables**|**Definition**|
|---|---|
|**Ridtil**|**ACCESS**|
|**esena access**<br>(%population)|= number of residential connections divided by the total population<br>**OPERATIONAL EFFICIENCY**<br>|
|**Energy sold per employee**<br>(MWh per employee)<br>|= Amount of generated consumed from the interconnected system divided<br>by the number of employees of the power supply entities for the whole<br>power market (MWh per employee)<br>**FINANCIAL EFFICIENCY**|
|**Tariff level**<br>(US$c per KWh)|= average tariff (US$c per KWh)|
|<br>**Carbon Emission Index**<br>**(CO2 ton/Kwh)**|**ENVIRONMENTAL SUSTAINABILITY**<br>= energy generated from each energy