rafmacalaba/datause-encoder-data huggingface dataset:
ES data for several countries around the world<sup>12</sup> and suggests that policy needs to expand the spectrum of firms that conduct R&D as a way to increase the national R&D intensity.

**Figure 13. R&D intensity, R&D incidence and GDP per capita across developing East Asian countries**

<!-- Start of picture text --> 6 25.0%<br>Vietnam Malaysia<br>Philippines<br>5<br>20.0%<br>Lao<br>Thailand<br>4 Cambodia<br>15.0%<br>3<br>10.0%<br>2<br>Indonesia,<br>5.0%<br>1<br>0 0.0%<br>3.1 3.3 3.5 3.7 3.9 4.1 4.3 4.5<br>Log GDP per capita (2011 PPP adjusted)<br>average log_Rdworker share of firms conducting R&D<br>Linear (average log_Rdworker) Linear (share of firms conducting R&D)<br>Source: Own elaboration based on ES data and WDI dataset<br>Note: R&D intensity is computed as the average logarithm of R&D per worker in US$, adjusted by sampling weights; R&D incidence<br>is computed as the share of firms doing R&D using sampling weights.<br>Share of firms<br>Average Log R&D per worker<br><!-- End of picture text --> ES data suggest that other innovation inputs, besides R&D, also play a relevant role in the innovation process. Results show that the proportion of firms that report innovation (of product or process) is much larger than reported formal R&D activities; in other words, a large fraction of firms that introduce innovation do not report formal R&D. This outcome is suggestive that other innovation inputs, besides R&D activities, are at play and could be seen as complementary factors of production in the innovation process, as highlighted in Cirera and Maloney (2017). Formal training for development of innovative products/processes is the most frequently used innovation input across the developing East Asian countries under analysis (Figure 14). On average, R&D inputs stands out as the second most frequently used input; a result that is probably driven by the Philippines and Vietnam as these countries present the top two highest R&D incidences (22 percent and 15.7, respectively) within the selected set of countries. Purchase of technology license is the third most frequently used innovation input. Overall, this result suggests that policies to boost innovation in this selected set of developing East Asian countries need to go beyond supporting R&D and encompass also other complementary inputs.

> 12 Drawing from ES data for several countries around the world, Cirera and Maloney (2017) find evidence that investment in R&D increases with GDP per capita and a large part of this increase is due to increased spending among the few firms doing R&D.

15
Policy Research Working Paper 8200

# **Abstract**

This study uses data from the complete computerization of agricultural leases in Malawi, a georeferenced farm survey, and satellite imagery to document the opportunities and challenges of land-based investment in novel ways. Although 1.5 million hectares, or 25 percent, of Malawi’s agricultural area is under agricultural estates, analysis shows that 70 percent has expired leases and 140,000 hectares are subject to overlapping claims. This reduces revenue from ground rent by up to US$35 millon per year or 5 percent of public spending and, by decreasing tenure security, may affect the productivity of land use. Indeed a 2006/07 survey shows large farms underperforming small ones in yield, productivity, and intensity of land use, while failing to generate positive spillovers. Recently passed Land Acts create opportunities to clarify the boundaries and lease status for existing estates as a first step toward systematic demarcation of customary estates. Failure to follow this sequence could exacerbate insecurity, with undesirable effects on productive performance.

This paper is a product of the Agriculture and Rural Development Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at kdeininger@worldbank.org or xia.fang.fx@gmail.com.

_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 its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Dang, H., P. Lanjouw, J. Luoto and D. McKenzie (2011). “Using Repeated Cross-sections to Explore Movements In and Out of Poverty,” Policy Research Working Paper Series 5550, The World Bank.

De Ferranti, D., G. Perry, D. Lederman, A. Valdes, and W. Foster (2005). _Beyond the City: The Rural Contribution to Development in Latin America and the Caribbean_ , World Bank, Washington DC.

De Janvry, Alain, M. Fafchamps, and E. Sadoulet (1991). “Peasant Household Behaviour with Missing Markets: Some Paradoxes Explained,” _Economic Journal_ 101, pp. 1400–1417. Deaton, A. (1987). “Estimation of Own- and Cross-Price Elasticities From Household Survey Data,” _Journal of Econometrics_ , vol. 36, pp. 7–30.

Deaton, A. (1988). “Quality, Quantity, and Spatial Variation of Price,” _American Economic Review_ , vol. 78 No 3, pp. 418–430.

Deaton, A. (1989a). “Rice Prices and income Distribution in Thailand: A Non-Parametric Analysis,” _Economic Journal_ , vol. 99 No 395, pp. 1–37.

Deaton, A. (1989b). “Household Survey Data and Pricing Policies in Developing Countries,” _The World Bank Economic Review_ , 3, pp. 183–210.

Deaton, A. (1990). “Price Elasticities from Survey Data,” _Journal of Econometrics_ , vol. 44, pp. 281–309.

Deaton, A. (1997). _The Analysis of Household Surveys. A Microeconometric Approach to Development Policy_ , John Hopkins University Press for the World Bank.

Deaton, A. and J. Muellbauer (1980). “An Almost Ideal Demand System,” _American Economic Review_ , vol 70, pp. 312–336.

Deaton, A., and F. Grimard (1992). “Demand Analysis and Tax Reform in Pakistan,” Living Standards Measurement Study, Working Paper No 85, The World Bank.

29
# **B Data Appendix**

All statistical codes to replicate the paper are available at https://github.com/ pierrebachas/Informality_Taxes_Redistribution. This includes the cleaning files for the micro data of each country’s survey, as well as all files generating the tables and figures of the paper.

## **B.1 Core Sample**

## **Inclusion Criteria**

Our dataset consists of 31 nationally representative household expenditure surveys. We use surveys which satisfy the following four criteria:

1. The household expenditure survey is nationally representative and dates from the 21st century.

2. The expenditure module(s) in the survey is structured as an open consumption diary, rather than a pre-fill diaries for a limited set of products.

3. The expenditure survey includes a variable for the place of purchase (data on where each item was purchased). The place of purchases are detailed enough for us to B.2.

apply our taxonomy of store types, as further outlined in section 4. The place of purchase variable rarely contains missing values, particularly for food, clothing and household goods product categories (see Figure A3).

## **Data Sources and Coverage**

We obtained the data principally from two sources: (i) the World Bank Microdata Library and (ii) National Statistical Agencies. Our first step for accessing data was to search the restricted-access World Bank Microdata Library for household Income and Expenditure, Living Standards, and Budget Surveys to see in which countries criteria (1)-(4) above appeared to be satisfied. The datasets which satisfied these criteria varied in their ease of access: for some countries, the micro data were accessible for download on the World Bank platform, others were licensed and required applications through the World Bank, which would in turn sometimes contact the country’s national statistical agency for approval. If a survey was listed without its micro through the World Bank platform, we reached directly the country’s’ statistical agency. Most countries for which we requested the data sent us the micro data, but in a few cases we could not obtain data 73
Figure 11: Education profile of Temporary employees. (Mid-1990s/Mid-2010s) <!-- Start of picture text --> 80%<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>Argentina Brazil Chile Mexico El Salvador<br>Incomplete primary (starting point) Incomplete primary (ending point)<br>Primary (starting point) Primary (ending point)<br>Secondary (starting point) Secondary (ending point)<br>Tertiary (starting point) Tertiary (ending point)<br><!-- End of picture text --> Source: Own calculations based on Household surveys However, it should be noted that the improvement of the educational profile of workers is a generalized trend in the countries considered and cannot be considered a specific characteristic of non-standard employment since it is also observed in standard wage employment and self-employed workers. Statistics regarding the educational profile of standard employees are included in Annex II of the paper.

Figure 12 presents the Kernel distribution of the labor income per working hour by country and type of employment. When we analyze what has happened at the salary level and distribution in the period under analysis, two important conclusions emerge. On the one hand, a shift to the right of the wage distribution is observed in all the countries analyzed, indicating an increase in their average. This growth in wages is simply a consequence of the economic growth experienced by these economies. Note that this average wage increase is also observed in the counterpart of standard employment in all cases..6 The second trend identified as generalized in the countries of study is the increase in the variance of the wage distribution. In fact, in most of the countries considered, non-standard employment wages currently show a significantly greater dispersion than that registered a decade ago. The only two exceptions are Chile and Peru in which the variance of the wage distribution of NSE shows a small decrease.

> 6As mentioned above, standard employment is calculated as the total number of employees who do not identify with any of the non-standard categories (temporary or part-time). However, since there are non-standard forms of employment not identified in the database, our standard employment category could, in fact, incorporate non-standard workers.

Page 16 of 51
capacity, expertise and strong working relations with governments (IEG 2011a: 6f). Specifically, donors might provide funding through the Bank rather than directly in circumstances where they do not want to be present in recipient countries themselves. For example, donors might want to delegate project implementation to the Bank in fragile countries because it allows diffusing accountability about aid effectiveness, because sending bilateral staff is politically sensitive, or because donors want to act in concert through the Bank to avoid harmful fragmentation in aid activities. We test for the relationship between trust fund and bilateral aid by directly including bilateral development assistance in some regressions.

Rhetoric by donors and the World Bank also suggests that trust funds are a useful instrument in fragile contexts. We expect fragile countries to be more likely to receive aid from trust funds rather than from IDA. On the one hand, the World Bank might be restricted by its legal mandate when governments in fragile contexts change repeatedly, making it virtually impossible to negotiate programs. Fragile states also have low CPIA scores by definition, limiting the IDA resources available for this country mechanically due to the allocation rule.<sup>12</sup> On the other hand, some bilateral donors may view the IDA performance‐based allocation system as under‐aiding fragile countries confronted with challenging situations. Moreover, some donors might be more concerned than other donors with security, refugee and other problems associated with specific fragile‐ and conflict‐ affected states. Such donors might be geographically proximate to the fragile situation, or have high reputation or economic stakes in the fragile country, such as former colonial powers. World Bank (2007) reports that RETF disbursements to fragile states increased from $130 million to $679 million between fiscal years 2002 and 2006.

Donors also use trust funds to fill “gaps in the multilateral system,” in particular to provide a rapid response to “emergencies such as natural disasters, disease outbreaks, and the end of armed conflict, where donors want to coordinate their bilateral aid and where the MDBs do not grant resources to engage on a sufficient scale” (IEG 2011a: 5). We test these motives by including dummy variables for disaster‐affected, post‐conflict, and fragile states.

Given the multitude of motives for using trust funds, we use multivariate statistical analysis that allows assessing the relative importance of these simultaneous motives while keeping time‐ invariant characteristics and year‐specific shocks constant.

> 12 A small number of post‐conflict countries receive supplemental IDA funding for a limited number of years.

8
||(29.16)|(6.84)|(16.47)|(0.06)|(7.77)|(0.04)|
|---|---|---|---|---|---|---|
|Firm age (years)|0.32***|-0.21**|-0.07|0|-0.1|0|
||(0.11)|(0.10)|(0.06)|0.00|(0.14)|0.00|
|Industry (base = min|ing)||||||
|Food & beverages|50.26|19.02|16.87*|-0.26***|3.8|-0.31***|
||(89.18)|(16.31)|(9.34)|(0.03)|(5.06)|(0.08)|
|Textiles and|||||||
|leather|-64|13.86*|27.70*|-0.19**|3.33|-0.29***|
||(49.92)|(7.39)|(14.67)|(0.09)|(2.74)|(0.07)|
|Pulp & paper|-45.68|47.79**|94.92|-0.27***|2.27|-0.33***|
||(77.88)|(20.04)|(69.00)|(0.04)|(2.70)|(0.07)|
|Chemicals|-25.34|27.33|85.24*|-0.15**|7.33*|-0.26***|
||(62.05)|(18.48)|(46.95)|(0.07)|(4.23)|(0.07)|
|Medical|-32.38|8.39|47.90***|<br>-0.28***|-0.05|-0.33***|
||(49.98)|(8.36)|(17.31)|(0.02)|(2.53)|(0.07)|
|Fiber, rubber &|-38.3|19.67|5.93|-0.26***|18.71|-0.32***|
|plastic|(65.87)|(26.08)|(20.49)|(0.04)|13.91)|(0.07)|
|Smelting|-49.93|4.12|10.07|-0.29***|0.03|-0.33***|
||(62.06)|(11.75)|(14.23)|(0.03)|(4.38)|(0.07)|
|Machinery|-102.24|11.2|9.34***|-0.29***|-0.87|-0.32***|
|manufacture|(87.87)|(12.63)|(3.44)|(0.02)|(1.05)|(0.06)|
|Utilities|154.48*|4.44|10.57|-0.12***|31.06|-0.27***|
||(90.40)|(16.83)|(36.76)|(0.04)|32.86)|(0.08)|
|Transportation|-42.63|23.17***|-0.19|-0.29***|3.27|-0.32***|
||(60.82)|(6.49)|(10.26)|(0.04)|(2.84)|(0.07)|
|Others|-22.62|10.17|13.15*|-0.24***|0.85|-0.30***|
||(32.06)|(15.22)|(7.11)|(0.03)|(2.27)|(0.06)|
|Time trend|12.82|1.67|2.52|0.00|3.28|0.00|
||(8.56)|(2.52)|(6.32)|(0.02)|(4.22)|(0.01)|
|Constant|404.84***|4.3|10.24|0.45***|30.09***|0.37***|
||(114.78)|(25.46)|(48.67)|(0.09)|(9.50)|(0.09)|
|No. of obs|1320 (4)|1128 (4)|1296(4)|1158 (4)|1229 (4)|1104 (4)|
|within_R_<sup>_2_</sup>|0.15|0.61|0.73|0.99|0.49|0.82|
|Between_R_<sup>_2_</sup>|0.16|0.52|0.84|0.97|0.33|0.61|
|overall_R_<sup>_2_</sup>|0.14|0.39|0.77|0.99|0.33|0.62|
|Breusch and Pagan L|agrangian Mu|ltiplier test f|or random e|ffects|||
|Test statistics: χ<sup>2</sup>(1)|0.06|0.14|0.05|71.64***|5.17**|23.77***|

Numbers in parentheses are standard errors of the estimated coefficients. ***, **, and * represent significance at the 1%, 5%, and 10% levels, respectively.
purposes.<sup>18</sup> Either way, if the index is treated as a proxy for entrepreneurship, the negative impact on inefficiency (higher impact on technical efficiency) does make sense.

With massive public investments roads over the past two decades, it appears that distance to Dhaka, or physically connectivity to the major urban centers, is no longer a problem. However, connectivity in the sense of access to public services, which are centered at the Thana HQ, remains a significant factor. The positive coefficient implies higher inefficiency. One key service for productivity growth would be access to technical advisory and extension services, and this seems to be the finding emerging from the data. Finally, the insignificance of the east-west dummy shows that living in the west is no longer a disadvantage, undoubtedly a benefit from the connectivity provided by the Jamuna Bridge and large investments by the government in roads.

# **5. Conclusions and policy implications**

Using three rounds of household panel surveys over a period of eight years, this paper looks at the relationship between farm size and agricultural productivity in Bangladesh. The empirical setting is important because features of Bangladesh’s agricultural economy help address some of the confounding factors that have dogged a ‘clean’ explanation of the inverse farm size-productivity relationship in other settings. Technology use and mechanization are widespread (with rental markets helping to overcome the need for lumpy investment in machinery); it has active factor markets (for labor and land leasing); panel data allow controlling for management skills; and several indicators are available to control for soil and land quality across farms.

Methodologically, the findings suggest that SPF models that ignore the inefficiency function are likely mis-specified, implying that the estimated farm size-productivity relationship may be misleading. Empirically, the findings show strong growth in productivity between 2000 and 2008, most of which appears to have been achieved between 2004 and 2008. This may be because productivity change in 2000-2004 cannot be detected as 2004 was a bad agricultural year due to widespread flooding in the country.

> 18 Indeed, fragmentation is found to be a highly significant determinant of farm diversification (results not shown for brevity).

24
# [Table 3 about here]

Table 3 presents the estimates of equation (22) without the inequality variables. Since the information on inequality is available for only a subset of the countries, Table 2 allowed estimation on the maximum number of observations available in the pooled sample. Note that the evidence in favor of a ‘Dynamic Penn effect’ is quite strong (for both with and without the ‘Trend’ variable) with the highly significant positive estimates of the coefficients of per capita GDP variable and exchange rate variable and non-rejection of the hypothesis of �� �1. The coefficient of the GDP deflator variable is positive, but non-significant. The strong positive relationship between PPP and exchange rate corroborates the prediction of Proposition 2. The inclusion or omission of the Trend variable has little or no effect on the estimates.

# [Table 4 about here]

Table 4 presents a more complete picture by reporting the estimates of equation (22) with the inequality. Proposition 5 predicts that the nature of the effect of inequality on PPP will vary between countries (mostly developing) with PPP less than exchange rates, and those with PPP equal to or greater than exchange rates (mostly affluent developed countries). Table 4 presents robust evidence of a positive relationship between PPP and intra-country inequality as predicted by Proposition 5 for countries with PPP less than the exchange rate.<sup>16</sup> Note from the table that the inclusion or omission of the Trend variable has little effect on the strong statistical significance of the inequality coefficient estimate in case of the low income countries. A comparison between the first two columns of estimates of Table 4 shows that the enforcement of the restriction that the exchange rate coefficient, �� =1, which means that we are estimating the changes in the price level index (PLI) rather than in the PPP, increases quite sharply the magnitude of the estimated inequality effect. Note, also, from the first and third columns of estimates, that the existence of the DPE (�� > 0, �� =1) is robust to the inclusion of the inequality variable and, as in Table 3, the Trend variable has no visible effect on the estimates.

# **5. Counterfactual PPPs : Methodology and Comparison with the ICP PPPs**

# **The Methodology**

> 16 In the ‘low income group’ in 98% cases PPP is less than the Exchange rate.

22
managers with representatives of various ministries, including Social Welfare, Education, Health, Labor, Finance, Agriculture, and Information.

FISE financed small projects that were managed and implemented by local governments and civil society organizations. The resources could be used for five project categories: social infrastructure (including construction of schools, health clinics, day care centers, latrines, and equipment for such facilities), socio-economic infrastructure (including water supply, sewerage, road rehabilitation, and irrigation), social services (including health, nutrition, and hygiene interventions, teacher training, etc.) institutional development (providing support to community operations and maintenance committees), and productive community investments (financing for group activities in agriculture, livestock, fishing, etc.).<sup>9</sup> However, they could not finance the operational budgets of implementing organizations. Appendix Figure 1 shows the location of all FISE projects disbursed between May 1993 and January 1996 – which constitutes our project-level data set – on a map of Ecuador. Each subdivision in the map corresponds to one canton (or _district_ ), and the three shaded areas denote the main geographic regions of the country: the Coast, the Sierra, and the Oriente (Eastern Region). Cantons in which p _arroquias_ received latrine projects are shaded black, and in which _parroquias_ received other projects (but no latrines) are dotted.

Before approaching the communities, FISE established central targets for the share of the budget that should be spent on different types of projects (at the aggregate level).<sup>10</sup> In addition, it adopted geographic targeting criteria, by allocating proportionally more resources to communities with higher numbers of poor individuals. These geographical poverty targets were established for aggregate resource transfers, and did not specify project _types_ for each individual locality. For the selection of project type, FISE employed a participatory, demand-driven approach. Regional offices organized meetings with community organizations and local government representatives to promote the program and to explain the guidelines for project application. In these sessions, FISE officials described the different types of projects for which resources were available, provided reference costs for each type, and explained the process through which

> 9 See World Bank, 1994 for more detail on the sub-project categories.

> 10 The term community is henceforth used as a synonym of – and interchangeably with – _parroquia_ (“parish”), the smallest administrative unit in Ecuador.

7