rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 9073

# **Abstract**

Using firm-level survey data on registered private firms collected by the World Bank’s Enterprise Surveys, this paper compares the level of labor productivity in 22 upper-middle-income countries and 11 high-income countries for which comparable data are available. The results show that labor productivity in the upper-middle-income countries is about 57.5 percent lower than in the high-income countries. The productivity difference is robust and holds for firms of different sizes and industries. The analysis uses the Oaxaca-Blinder decomposition to identify the sources of the productivity gap. It finds that the endowment effect and the structural effect contribute roughly equally to the productivity gap. Several firm- and country-level variables determine the productivity gap. The biggest contributors via the endowment effect include tertiary education attainment, law and order, and quality management proxied by international quality certification. Factors that contribute most via the structural effect include market size, secondary education attainment, and law and order. Thus, the results underline the importance of human capital, institutions, and market size for closing the productivity gap between the upper-middle-income and high-income countries.

This paper is a product of the Global Indicators Group, Development Economics. 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 mamin@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
is measured as the number of coffee trees per sq km in 1999, compiled from the Rwanda coffee census. We also include data on road density at the municipality level, average annual temperature, total precipitation, and coffee suitability.

# **4 Empirical Strategy**

Our baseline specification is a difference-in-difference (DID) design, where we compare the differences in test scores of students who were exposed to coffee mills in early life to those born earlier in the community and hence not exposed to the mills in early life, with counterparts born in communities without a coffee mill. Essentially, our estimation strategy leverages plausibly exogenous variations in the establishments of the coffee mills across space and time (see Figure 7
. high population growth with equal shares of different land types given to all heirs, are either no longer in place, e.g. because workers are joining the nonfarm sector in large numbers (Platteau and Baland 2001). Alternatively, institutional arrangements such as land markets -possibly with a right of first refusal by neighbors- will need to be in place to deal with them (van Dijk and Kopeva 2006). Where this was not the case, consolidation programs -in some cases implemented at considerable cost- were unsustainable and the situation soon reverted to what had been in place previously. Recent pilot consolidation efforts in Eastern Europe hold a number of additional lessons. First, achievements in terms of the number of land transactions triggered by such programs remained below expectations, partly because part of fragmentation had been voluntary and the programs did not deal with broader land policy issues.<sup>8</sup> Second, efforts need to include all relevant stakeholders and ideally be integrated into a broader plan for territorial development.<sup>9</sup> Finally, to ensure sustainability and continued adjustment through subsequent

> 7 More recent evidence from India shows that plot sizes too small to allow mechanized cultivation significantly reduce agricultural productivity (Foster and Rosenzweig 2010), although this is less an issue of fragmentation than of a general decline in farm sizes. 8 In a consolidation pilot undertaken in 2007 to 2009 in 6 Moldovan villages with 11,500 ha and 27,000 parcels, participation was about 40%. Partly because it involved a systematic review of the land registry, this led to a reduction in the number of parcels per owner from 3.74 to 3.23, an increase in average parcel size from 0.45 to 0.59 ha, and an increase in the mean area per holding from 2.21 to 2.93 ha, largely by owners selling plots that were too small or inconveniently located (AGREX 2011). 9 In the Moldova case referred to above,
# **g. Worker Training**<sup>**35**</sup>

Worker training is a right in many countries. Ongoing upgrading of the work force through training, particularly in rapidly evolving industries, is a central element of the national innovation system.

**_Training tends to have a positive impact on productivity_ . . .** In general, the available rigorous empirical evaluations of training programs find that training increases firm-level productivity, (Tan and Lopez-Acevedo, 2003; Barrera and Higuera, 2004 among others for LAC). The impact on subsequent earnings is less clear, the productivity increases can translate into higher wage premiums but especially for skilled workers **.** Firm investments in training tend to pay off particularly when training takes place in-house and benefits already skilled workers. Further, it has been found that increased continuity of training leads to larger impact on productivity than does intermittent training.

_..._ **_and is complementary to firm R&D and technology adoption_** _._ Firm-level data show that firms that are capital intensive and/or invest in R&D and technological change are more likely to train workers (Barrera and Higuera, 2004; Gill, Dar, and Fluitman, 1998, and Tan and Batra, 1995b and 1997).

**_Larger firms are more likely to provide training_** in the Caribbean, Colombia, Mexico, and LAC in general.<sup>36</sup> Small firms may be more constrained by resources, lack knowledge about training benefits, invest less and have higher labor turnover rates than large firms (De Ferranti, 2003).  Some evidence from Mexico suggests that membership of a union raises the likelihood of receiving training (Lopez Acevedo 2002).

**_Training is not a substitute for good schools._** Firms overwhelmingly choose to train skilled (secondary education or above) workers. This is an exceptionally robust finding that is salient in cross-country household surveys, administrative databases
010|27042|Senegal|0.802|0.024|3850|
|Jordan|0.667|0.015|17023|Sierra Leone|0.668|0.030|2209|
|||||South Africa|0.786|0.040|2407|
|South Asia||||Tanzania|0.659|0.021|5619|
|Afghanistan|0.618|0.016|7585|Togo|0.825|0.043|1615|
|Bangladesh|0.820|0.010|12031|Uganda|0.735|0.020|4176|
|India|0.744|0.003|151142|Zambia|0.746|0.016|5595|
|Nepal|0.658|0.015|5574|Zimbabwe|0.707|0.024|3369|
|Pakistan|0.808|0.006|40964|||||

_Notes_ : This table presents the estimated share of the intergenerational component using the Bingley and Cappellari (2019) method for each of the 53 developing countries in the Demographic and Health Surveys (DHS) using the full sample.

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Messenger. The tested campaigns consisted of short video clips that in total amounted to approximately 25 minutes, in line with communication research suggesting that short video clips are needed for effective social media marketing campaigns (Constantinides, 2014). We recruited individuals ages 18-to-24 years living in New Delhi and six other northern Indian cities using a Facebook ad campaign. We collected self-reported and objective online outcomes and measured impacts one week and four months after program exposure. To understand whether implicit messaging was more effective than explicit messaging, the treatment group was randomly exposed to either a humorous fake reality TV drama on gender norms and misconceptions (implicit) or a docuseries about VAW and gender discrimination with clear calls to action (explicit).

Our findings show that both edutainment formats worked, with effects varying for different outcomes. Our objective viewership data shows that take-up rates for the humorous drama were twice as high compared to the more information-focused docuseries. On effectiveness, however, neither format dominated in the one-week follow up survey. While the drama was more effective at raising knowledge and reshaping attitudes related to gender norms and VAW (intent-to-treat effects oscillated between 0.16 and 0.21 standard deviations), the docuseries was more impactful in increasing willingness to share video clips with friends (5 p.p.) and promoting online information-seeking behaviors (10 p.p.).

In the four-month survey, individuals assigned to the docuseries were 91% (7.5 p.p.) more likely to add the frame “End Violence Against Women” to their Facebook profile picture. This effect along with users’ greater willingness to share campaign videos with online friends are important outcomes for social media campaigns designed to update perceptions of social norms within online communities. Moreover, we document spillover effects in the long-term. We found that about one and a half years after the frame was first presented to the respondents, it was used by more than 34,000 people all over the world, an amplification of about 55 times the initial audience size
comparing the income and expenditures of self‐employed workers with those of wage and salary earners. The ratio of business income reported to tax authorities over real business income as of 2014 was estimated by applying the same method employed in Sung (1999, 2008). Business income reported to tax authorities per household was estimated with the real business income and income reporting ratio obtained in the previous stage. The PIT burden was calculated based on the business income reported to tax authorities as well as demographics and expenditure data obtained from HIES. However, it was assumed that wage and salary income were reported correctly. The detailed methodology is described in the Appendix 2. Following are the three scenarios employed.

**Scenario A** ( _counterfactual scenario 1: baseline_ ): Average PIT burden per household in 2014 was estimated under the assumption that business income earners reported their income based on the past increasing trend without the intervention of TIETP. The average reported business income in 2014 was estimated by extrapolating the past ratio of business income earners’ reported income to their real income. In this study, Sung’s estimate (1999) for the ratio of business income earners’ reported income to real income in 1996 (47.7 percent) and another Sung estimate (2008) for 2001 (53.9 percent) were used to linearly extrapolate the estimate for 2014.<sup>53</sup> It should be noted that the 2001 estimate was used for extrapolation, considering that the estimates between 1997 and 2000 were outliers due to the financial crisis in Korea, and that if 2001 estimate affected by TIETP at the early stages of TIETP introduction were extrapolated as a baseline, it would underestimate the effect of TIETP when compared to the observable. In other words, considering that the extrapolation using inflated data would result in a conservative estimate of the TIETP effect, we compromised by using the 2001 estimate.

It was assumed that this counterfactual scenario only included tax‐base‐broadening effects caused by factors other than TIETP.
Relative income rather than total income may affect satisfaction, and if ignored, may result in biased estimates (Borah _et al._ , 2018). We include dummy variables to indicate the relative position of the household in the reference group`s distribution of household income quartiles (Appendix A, Table A.8). The reference group is determined for each year and consists of individuals living in households with a similar size in the same primary sampling units. To ensure stability, we only consider the number of households in the reference group as having 10 or more households. We report estimates of the scale parameters for the POL model only, since the variable used to define the reference groups is largely time-invariant, especially at the primary sampling unit level. Controlling for the reference group decreases the child scale parameter to 0.05 in the POL model but does not change the baseline elasticity. More importantly, we still obtain the earlier result that an additional child has a smaller effect compared to an additional adult (Table 5, row 2).<sup>21</sup> We also analyze the other satisfaction variables in the RLMS as alternative dependent variables for the subjective wealth variables, which are satisfaction with one’s life and satisfaction with one’s economic conditions. The estimated coefficients on household income and household size are still statistically significant as expected (Appendix A, Table A.9). To save space, we only report the scale parameters derived from the regressions for life satisfaction (Table 5, row 3). The estimation results of the BUC model are robust with the adult scale parameter of about 0.6 and child scale parameter about 0.04.<sup>22</sup> As a check on the total household income variable, we generate a new total household income by summing all the net incomes reported by household members (Appendix A, Table A.10). Yet, the estimated scale parameters of 0.3 for adults and 0.06
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# _2.b.5. Parents’ and Community Characteristics_

69. Following the existing practice, we control for the average level of education of fathers and mothers of the students enrolled in the school. We also report whether at least one parent reports being unemployed, and among the possible occupations of the employed parents, we give special attention to farming. In order to further account for parents‟ preferences for education we register the number of books kept in the households (self-reported by parents), and we ask parents whether they agree or disagree (on a 5-point Likert scale) with the following statement: “There is not much point in sending my children to school, because education won‟t help them to find a better job when they grow up.” We report the proportion of parents in each school who disagree or strongly disagree with the statement. Finally, following Filmer and Pritchett (2001) we construct an index of household socio-economic status based on parents‟ answer to 13 questions aimed at registering whether the household owned a number of assets, such as a washing machine, a fridge, an oven, a car, a mobile phone etc. We conduct principal factor analysis on the answers to the 13 questions and report the resulting first factor, which represents our index of household socioeconomic status.<sup>26</sup> 70. While ethnic fragmentation is not a problem in Albania – only 2.5% of the surveyed stakeholders speak a language different than Albanian (Greek) in their households – divisions within the community based on wealth, and/or education and/or landholding, and/or political affiliation may prevent parents from collectively participate in the school, possibly leading to lower education outcomes.<sup>27</sup> In order to measure the extent of divide within the community we asked all surveyed stakeholders the following question: _“There are often differences between people living in the same village/neighborhood. For example, difference in wealth,
involving possible Doha Development Agenda reforms. Using the World Bank’s $2/day poverty line, we find that multilateral trade reforms do in fact reduce poverty in China. The biggest reductions occur in the rural areas – largely as a result of higher prices for farm products. Since this is where the bulk of the poor in China reside, an overall reduction in poverty follows.

Urban poverty falls in two of the three household groups considered in this analysis, since the increased demand for China’s products in world markets boosts factor earnings sufficiently to offset the impact of higher food prices. For the remaining group – which is heavily dependent on transfer payments -- we assume that indexation of these payments will largely offset the adverse consequences of higher prices. However, a decline in other income sources is sufficient to cause an increase in poverty, and this increase is large enough to boost the overall urban poverty headcount. However, the urban poor only represent 5% of the total poor in China and thus the national poverty headcount falls.

We also explore the implications of complementary reforms in China – in particular increased investments in rural education aimed at equalizing per capita spending between rural and urban areas. This boosts rural enrollments by 16% which has the twin benefits of increasing labor productivity, as well as enhancing the mobility of the rural labor force, thereby putting these workers in a better position to benefit from trade reforms. Our analysis takes account of the cost of funding these additional students, as well as the reduction in the workforce that results from having more pupils in school. Nevertheless, these reforms generate very substantial gains for China’s economy. They also serve to boost rural incomes and reduce the incidence of rural poverty. Indeed, when combined with global trade liberalization, poverty in China is estimated to drop by about 55 million people.

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Policy Research Working Paper 9419

# **Abstract**

A model of Covid-19 transmission among locations within a country has been developed that is (1) implementable anywhere spatially-disaggregated Covid-19 infection data are available; (2) scalable for locations of different sizes, from individual regions to countries of continental scale; (3) reliant solely on data that are free and open to public access; (4) grounded in a rigorous, proven methodology; and (5) capable of forecasting future hotspots with enough accuracy to provide useful alerts. Applications to the United States, the Philippines, and South Africa’s Western Cape province demonstrate the model’s usefulness. The model variables include indicators of interactions among infected residents, locally and at a greater distance, with infection dynamics captured by a Gompertz growth model. The model results for all three countries suggest that local infection growth is affected by the scale of infections in relatively distant places. Forecasts of hotspots 14 and 28 days in advance, using only information available on the first day of the forecast, indicate an imperfect but nonetheless informative identification of actual hotspots.

This paper is a product of the Development Research Group, Development Economics and the Urban, Disaster Risk Management, Resilience and Land Global Practice.. 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 sdasgupta@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not
data consists of gridded meteorological observations from weather stations interpolated on a 25 × 25 km grid. They are available on a daily basis from 1979 in the European Union and its neighboring countries, including Tunisia. We selected variables for minimum and maximum air temperatures (in Celsius degrees) and sum of precipitation (mm/day) to calculate the Standardized Precipitation Evapotranspiration Index (SPEI), our main treatment measure. The SPEI represents a stateof-the-science indicator for measuring the impact of increased temperatures on water demand (VicenteSerrano et al., 2010; Chiang et al., 2021). Since climate grids come at a finer spatial resolution than our administrative unit of analysis, we calculated SPEI values for each grid point falling within each administrative unit. We then weighted the SPEI value of each grid data point with the resident population.

Finally, we collapsed the data to obtain medians of population-weighted SPEI values in each governorate 6
# **2.2.1 Evaluation of GP presidents under PVP**

In order to incentivize GP presidents to work with the VPRC to improve responsiveness and transparency in local governance, the design of the PVP project also included a program-wide performance-based financial incentive in its first phase of implementation. To implement this performance-based scheme, each GP president was assessed on a range of indicators that related to their performance on the overarching function of the GP, i.e. the delivery of public services and targeted safety net programs, and their role in overseeing the activities of the VPRCs.

To assess performance, PVP developed evaluation criteria based on project monitoring data. A team of external evaluators used a combination of project monitoring data, and random field verification visits to implement the evaluations. To avoid any semblance of bias in the evaluation process, the evaluation teams were always from a different district from the GP that they were assigned to evaluate which makes it very unlikely that they were familiar to the GP prior to visiting it. Evaluators also consisted of people intimately familiar with the functioning of GPs— such as retired local bureaucrats and PVP members. A team of 5-6 such evaluators visited the GP for a period of 2-4 days to conduct this evaluation.

A predetermined scoring system was then used to convert these indicators or evaluation criteria into scores; with a maximum possible score of 100. An absolute score was used to determine the threshold for the performance incentive, with cutoffs of 70 and higher, 69-55, and less than 55 used to assign letter grades A, B, and C, respectively. In this first phase, GPs with a letter grade A qualified for a financial incentive from the project.

Project monitoring data used in these evaluations were collected by the VPRC, which delivered all interventions under the PVP project; and they were verified through a multi-stage process. These data were collected through standardized reporting formats and informed a range of project functions from the identification of target and beneficiary populations to the tracking of expenditures and process-related outcomes