rafmacalaba/data-use-mentions-extended huggingface dataset:
Market expansion also directly affects the choice of technique in grain mills and bakeries, which it does not seem to do in the production of cinder blocks. This also comes out in Table 5 and Table 7, where market expansion is seen to reduce TFPR in bakeries per the first table by a higher proportion than in Table 7. Part of the effect seen in Table 5 must therefore be associated with the choice of the scale or factor intensity in this case also. The picture is similar in grain mills, where market expansion reduces TFPR in Table 5, but does not have any such effect in Table 7, suggesting that the effects we read in Table 5 are influences transmitted via choice of the scale or technique.

_H. Determination of TFPR in textiles, garments, footwear, plastic products, wood work, metal works, and the furniture industry_ How does the pattern of results reported for the four industries in Tables 3 to 7 hold up across the other seven industries? Do market size, transport costs, and entry regulation affect aggregate productivity across any of these industries as they seem to do in the production of cinder blocks? Or, is the effect of any one of the three factors contrary to what economic theory predicts?

We address this question by analyzing data on seven four‐digit ISIC industries and report our findings in Tables 8 through to 11. The tables relate to growth in TFPR only, to which our comparison across the 11 industries is limited. This is because we do not have unit product price data for the industries that the four tables cover.

Estimation and test results on the textiles industry (ISIC 1710), wearing apparel (ISIC 1810) and the footwear industry (ISIC 1920) are reported in Tables 8 and 10. Results for wood processing and wood products (ISIC 2000), manufacturing of plastic products (ISIC 2520), structural metal products (ISIC 2811) and furniture making (ISIC 3610) are reported in Tables 9 and 11.

The first column of Table 8
Finally, it is important to mention that this paper does not consider the role of essential sectors or workers (whose jobs are not affected by social distancing measures) since there is substantial heterogeneity in these policies between and within countries that cannot be fully accounted for in this paper.<sup>4</sup> Our individual-level measures of WFH amenability, however, can be used to assess the potential impacts of essential work policies.

The rest of this paper is structured as follows. Section 2 describes the data and the main features of the methodology. Section 3 describes the results and Section 4 concludes. The paper includes an Appendix with more detailed information on the methodology, and the estimated indexes by detailed socioeconomic group and country.

# **2. Data**

We use three data sets covering 53 countries at different levels of development to estimate our WFH measure (see Table 1). First, we use the Surveys of Adult Skills of PIAAC (Programme for the International Assessment of Adult Competencies) for 35 countries. This survey collects information about working-age individuals and covers both rural and urban areas. Second, we use the STEP (Skills Towards Employability and Productivity) surveys for 15 developing countries.<sup>5</sup> The surveys are representative of urban areas (except Sri Lanka and the Lao People’s Democratic Republic, which included both urban and rural areas) and collect information about working-age individuals. Finally, we use the Labor Market Panel Surveys (LMPS) for three countries in the Middle East and North Africa (MENA) region, namely the Arab Republic of Egypt, Jordan and Tunisia. These are standard labor force surveys that, in addition to the typical labor market information, also collect data about specific tasks carried out at work. Our final sample for all three data sets includes employed individuals ages 16 to 64 years.

> 4  Garrote Sanchez, Gomez Parra, Ozden, & Rijkers (2020) consider the role of essential workers in their assessment of WFH measures
measures such as the costs (including time involved) of exporting and importing, the quality of trade- and transport-related infrastructure, and proxy measures (Figure 11). However, the average EMDE’s overall “trade across borders” score in the Doing Business survey improved by 11 percentage points between DB2007 and DB2020.

Some of this progress has been driven by trade-related reforms, again with increased momentum visible in the three years prior and during the global recession. Thus, the number of trade-related reforms in EMDEs increased from 24 to 37 between DB2008 and DB2010. However, these numbers imply that still only a minority of EMDEs were undertaking reforms that lowered the cost and time required to import and export. Reform momentum slowed after 2010. Since DB2017, however, there seems to have been some renewed vigor in trade reform, with the number of relevant reforms rising to 34 in that year. In contrast to these efforts to lower within-border trade-related costs, G20 economies have imposed a growing number of tariffs and non-tariff restrictions on trade (WTO 2019).

# 4.1.6 Energy subsidies

> 23 Reform spurts are improvements in one or more of the Worldwide Governance Indicators that are sufficiently large to exceed the country-specific average by more than 2 standard deviations. Reform setbacks are similarly-sized declines in the indicators.
- Patterson, C. J., E. L. Sutfin, and M. Fulcher. (2004). “Division of Labor among Lesbian and Heterosexual Parenting Couples: Correlates of Specialized Versus Shared Patterns.” _Journal of Adult Development_ , 11, pp. 179–189.

- Posel, D. and E. Grapsa. (2017). “Gender Divisions in the Real Time of the Elderly in South Africa.” In: Connelly R., Kongar E. (eds.) _Gender and Time Use in a Global Context_ . Palgrave Macmillan, New York.

- Quisumbing, A., R. J., P. Estudillo, and K. Otsuka. (2004). _Land and Schooling: Transferring Wealth across Generations_ . The Johns Hopkins University Press.

- Ranchhod, V., and M. Wittenberg. (2016). “The Social Pension and Time Allocation in Poor South African Households.” In Timothy Besley (Ed.), _Contemporary Issues in Development Economics_ (pp. 91–111). Hampshire, England: Palgrave Macmillan.

- Rao S. (2017). “Women and the Urban Economy in India: Insights from the Data on Migration.” In: Connelly R., Kongar E. (eds) _Gender and Time Use in a Global Context_ . Palgrave Macmillan, New York.

- Reid, M. G. (1934). _Economics of Household Production_ . New York: John Wiley and Sons, Inc.

- Rogers, Martha (2014). “Forest Access and Human Capital Accumulation.” In _Environment and Development: Essays on the Link between Household Welfare and the Environment in Developing Countries_ , Ph.D. Dissertation, University of Minnesota.

- Rothblum E.D. (2017). “Division of Workforce and Domestic Labor Among Same-Sex Couples.” In: Connelly R., Kongar E. (eds) _Gender and Time Use in a Global Context_ . Palgrave Macmillan, New York.

- Sayer,
the analysis of urban costs. First, we discuss the construction of the sample of papers used for the meta-analysis, and second, the urban cost data.

> 2 For more evidence see Bacolod et al. 2009; Abel et al., 2012; Lindley and Machin, 2014 for the United States; Di Addario and Patacchini, 2008 for Italy; Groot and de Groot, 2014 for the Netherlands.

> 3 In France Combes et al. (2013) find that urban costs are much lower when the physical growth of cities is not restricted.

8
|10.5|10.5|10.5|10.5|10.6|10.6|10.6|10.5|10.5|
|VEN|Applied|10.8|10.9|10.9|10.7|10.9|10.9|10.9|7.5|4.1|3.9|4.0|
||MFN|13.3|13.4|13.4|13.2|13.4|13.4|13.4|13.0|13.1|12.8|13.9|
|LAC average|Applied|6.7|6.6|6.2|6.4|6.0|5.9|6.4|5.2|4.6|4.9|4.1|
||MFN|9.1|8.9|9.0|8.9|8.7|8.7|8.7|8.7|8.6|8.6|8.7|

Source: Author’s calculation based on UNCTAD TRAINS tariff data. Note: This table displays Colombia’s most-favored nation (MFN) and applied tariffs over time in its LAC destinations markets. MFN tariffs measure the normal non-discriminatory tariffs charged on imports from Colombia. Applied refers to the effectively applied tariff, which is defined as the lowest available tariff. If a preferential tariff exists, it will be used as the effectively applied tariff. Otherwise, the MFN applied tariff will be used. The LAC average reports Colombia’s simple average of MFN and applied import tariff rates across the 17 LAC destination markets, respectively.

lations over time, we document the share of all regulations entered before vs. after 2007, the first year of data collection, and the share remained active vs. abolished in
was an increase of 5.2 percentage points. The underestimation of poverty changes is in line with the underestimation of income losses presented in Figure 10.

**Table 3. Change in poverty between 2019 and 2020. In percentage points**

||US$ 2.25/day|US$ 3.65/day|US$ 6.85/day|
|---|---|---|---|
|Quarter 1|0.82|0.56|0.76|
|Quarter 2|7.02|8.49|10.81|
|Quarter 3|6.80|8.52|10.75|
|Quarter 4|5.06|6.87|8.58|
|Average|4.92|6.11|7.72|
|Simulation|2.67|3.99|5.23|

Source: PNAD-C 2019 and 2020.

# **5 Conclusions**

<mark>In this study we estimated the distributional impacts of the pandemic in five developing countries: Brazil, Sri Lanka, the Philippines, South Africa, and Türkiye. We used a macro-micro simulation approach to capture the impacts of the pandemic via three channels – job loss, labor income declines, and changes in remittances – on total household per capita income/consumption and on</mark> the shares of poor, vulnerable, and middle-class populations in each country during 2020.

<mark>We analyzed the accuracy of using employment projections based on GDP-employment elasticities for 15 developing countries by comparing the projected employment levels with observed 2020 values. We also validated our microsimulation estimations for Brazil using 2019</mark> and 2020 microdata from the PNAD-Contínua.

<mark>Our findings showed, first, that employment estimates for 2020 based on elasticities were reasonably accurate in 11 of the 15 countries. However, in the remaining four countries the projections considerably overestimated employment levels and therefore underestimated
different locations are more vulnerable

> 10 Maize yield estimates data had many fewer missing data points.

> 11 TA population estimates are derived from NSO (2008). TA area is derived from publicly available geospatial data. TA population density is calculated by the authors as population divided by area.

> 12 The accessibility index captures density of road networks and proximity to urban centers.

> 13 - Maps of the constituencies were accessed at <u>https://mec.org.mw/maps district/</u> to allow linking to TAs, since our - data lacks GPS-confirmed constituency information.  Election results were accessed at: https://mec.org.mw/2014 <u>tripartite-elections</u> for the 2014 elections and https://mec.org.mw/2009-general-elections/ for the 2009 elections.

15
profits from NA in proportion to dividends.<sup>23</sup> We present results in Figure 7, which documents the share of income flowing to the top 1% and 0.1%, using our baseline and alternative methodologies. For the top 1% share, the gap is approximately 3 - 4 p.p. across the period - in recent years our baseline measure is approximately 28 - 30% vs. 25 - 26% when we do not use the corporate ownership data. However, the gap is much larger when we consider the top 0.1% share. Our baseline estimates suggest the top 0.1% earners receive between 18 - 20% of total income in recent years, whereas those figures are in the range 10 - 12% using the alternative methodology. These results suggest that using realized dividend income to adjust for undistributed corporate profits might be an incomplete exercise, and detailed data on corporate ownership might provide a important lens for measurement of top income inequality.

# **7.2 Persistence at the top**

Our key results show a substantial persistence of the share of total income flowing to the highest earners individuals across time. A distinct but equally important question relates to the identity of those individuals at the top of the income distribution (Acciari _et al._ , 2022, Auten _et al._ , 2013, H ́erault _et al._ , 2022). In one scenario, even if the share of income flowing to the top is stable, the identity of those highest earners changes substantially as top firms are challenged by incumbents; as the demand for skills change in the job markets; and as innovators gain access to new income generating activities. Alternatively, the same individuals occupy the top of the income distribution over time – either because the majority of their income are returns to wealth that persist over time, because their successful firms are unchallenged in the market, or because opportunities for other to achieve high incomes are hampered by
. Specifically, the section documented whether any transfers had occurred between the woman and the rest of household members as well as the amounts of the transfers in either direction. The module was intended to measure potential intra-household reallocation of income in response to the intervention, i.e., whether the women engaging in public works handed over their income to their husbands.

# **4.2. Baseline balance and attrition**

> 10 It is important to keep this change in survey design in mind when looking at changes in the levels of employment and earnings from baseline to midline or endline, as this change would impact the four groups (AD) equally. Indeed, we observe a much higher and similar rate of employment for women in control households at midline and endline, suggesting that the weekly surveys did capture volatile work better than the standard 7-day recall design.

12
a given country comprise issues by residents in domestic currency targeted at resident investors, whereas international debt securities (i.e. Quarterly Review Table 11) are the ones targeted at non-residents (a) in domestic currency on the domestic market, (b) in domestic and foreign currency on the international market, plus the issues (c) in foreign currency in the domestic market (further information can be found in the Guide to the international financial statistics, http://www.bis.org/publ/bppdf/bispap14.htm).

As two different collection systems are used (s-b-s for international debt securities and aggregated data for domestic debt securities), some overlap (between domestic debt securities and international debt securities) and inconsistencies (classification of issuers) might remain which differs from country to country.

Country authorities’ websites were used to re-confirm and fill in some of the gaps in the data.
-13-

Among a limited but fairly representative sample of 26 utilities, only 10 (or under 40%) evidenced good supply quality based on thelr record of load shedding, sudden blackouts, brownouts, and voltage and frequency fluctuations. Even more serious Is the finding that about 25% of these 26 power companies continued to have poor service quality after over 10 years (at least three projects) of Bank Involvement In the sector. The loss levels also exhibited quite similar characteristics.

# Cost of Supplv and Prices

The average cost of service based on such financial data as operating costs shows little change during the study period, although Inflation and exchange rate changes have made It difficult to make comparisons across countrles or over time. The economic costs are likely to be higher because assets have not been revalued In all cases and the opportunity costs of resources tend to be greater than the corresponding market values (e.g., the financial, rates of return on assets are low compared with the opportunity cost of capital).

In real terms, tariffs have not kept up with financial costs even In financial terms. The steady deterloration In the average operating ratio over the past two decades from 0.65 In the 1966-73 period to 0.80 during 1980-85, provides supporting, but not necessarily conclusive, evidence. Despite much emphasis by the Bank on -economic efficiency pricing, relatively modest progress has been made on a global basis except In the cases of specific countries where marginal cost-based tariff studies have been partially or fully Implemented. A lack of data, however, prevents a general comparison of tariffs with marginal costs.
across the study countries suggest that on-farm trees are also a vital part of larger rural landscapes. As elsewhere in the developing world (Sayer et al., 2013), policies and practices designed to improve the management of such trees in Africa therefore hold significant promise for helping to reconcile the sometimes conflicting goals of reducing rural poverty, conserving biodiversity, and mitigating climate change.

Our second major finding is that trees on farms deliver sizeable economic benefits to rural households. Across the rural population as a whole, production from trees on farms accounts on average only for 6% of total annual gross income. Yet, this increases to 17% on average for those households growing trees on their farms. By way of comparison, these results are similar to available evidence on forest and environmental income. For example, a recent study using national-scale data from Mexico (LópezFeldman, 2014) found that forest and other environmental resources contributed 6.2% to total incomes for Mexican rural households. For those households living in or near forests in a cross-national comparative study (Angelsen et al., 2014), income from natural forests and forest plantations accounted for 21% of total household income. Together, these studies suggest that trees—in forests and outside forests—provide significant income to rural households in Africa, especially but not only to those living with trees nearby or on their land.

Finally, results from models of the determinants of the adoption of and land allocation to trees on farms highlight the importance of national institutional and policy contexts in understanding differences in onfarm tree growing. Together they account for more than 40 percent of the explained variation of the models. Proximity to forests proves also an important predictor. Households with more land tend to allocate more of their land to trees (both cash crop and fruit trees). Female-headed households tend to be less engaged in tree growing, with the effect being largest for tree cash crops (possibly linked to higher land tenure insecurity for female farmers and consistent with the higher nutritional value of
crude measure of productivity. We also use indicators for whether the firm hires relatives from outside the household. A similar measure indicates whether the firm hires any non-relatives.<sup>18</sup>

# **2.4. Firm Dynamics**

Since the ELMPS follows households in four waves, 1998, 2006, 2012 and 2018, we can trace the dynamics of firms in our data set. Dynamics can occur over three pairs of waves: 1998-2006, 2006-2012, or 20122018. An observation for our dynamic model thus has data from a base wave and a subsequent wave, e.g. for 1998-2006 the base wave is 1998 and the subsequent wave is 2006.

Creating a panel of firms from a household survey presents a number of complexities. We restrict all analyses to cases where the household was observed in both the base and subsequent wave of a pair, so we do not classify a firm as being created simply because a household joined our data set, nor a firm exited because the household attrited. We do track splits, so cases such as where an unmarried son may have had a household enterprise and then took it with him to his new household when he married and moved out (split) are captured as a firm surviving, so long as we successfully located the split household. We define an enterprise that existed in the base wave as having survived over a pair of waves if at least one household member still has an enterprise of the same economic activity (identified on the one-digit level using ISIC 4 coding). We examine the outcome of exit (closure) as the complement to an enterprise surviving. We also consider the formation of new household enterprises, that is, among households that were not engaging in an economic activity in the base wave of a pair, new enterprises in the subsequent wave. We further consider – among enterprises that survived across a pair of waves – the dynamics of (in)formalization, that is, changing formality status between the base and subsequent
0.191)|(0.202)|(0.267)|(0.205)|(0.202)|(0.301)|(0.218)|(0.232)|
|Lagged Change in GDP|0.127***|0.0914**|0.0971**|||||||
||(0.0356)|(0.0361)|(0.0372)|||||||
|Lagged Change in Total Government Spending||||0.247|0.259|0.204||||
|||||(0.169)|(0.158)|(0.166)||||
|Change in CPIA PolicyIndicator|||||||0.0111***|0.00706|0.00856**|
||||||||(0.00362)|(0.00428)|(0.00396)|
|_First-Stage F-Statistic_|11.81|26.66|21.39||||8.7|21.03|16.66|
|_Stock-Yogo Weak Identification Test Statistic_||||2.90|2.93|4.06||||
|_Number of Observations_|2782|1493|1937|2702|1452|1883|2516|1386|1755|
|_Number of Countries_<br>Note: *** (**) (*) denotes significance at the 1 (<br>estimated using pooled country-year data and in<br>by lagged GDP. Panel A reports OLS estimates of<br>lagged growth, (b) controlling for lagged changes<br>(20%) maximal IV size is 3.63 (3.95). The three co<br>countries where disbursements on loans from of
# **Firms Far Up! Productivity, Agglomeration and High-Growth Firms in Ethiopia**

# **Arti Grover**

_World Bank Group_

**_Keywords_** : High-growth firms; Firm growth; Productivity; Agglomeration; Ethiopia

# **_JEL Classification_** : D24, L11, L25

**Acknowledgements** : I would like to thank Yahia Ziad Abuhashem Aida and Nicolas Pierre Gonne for their excellent research assistance on this paper. The paper has benefited immensely from discussions with William F. Maloney, Denis Medvedev, Lars Moller, Michel Serafinelli and Eyerusalem Siba. I thank Katie McWilliams for her assistance on distance data, and Paulo Bastos and Megha Mukim for sharing the Ethiopian manufacturing plant-level data.
S.M. Jones, C.P. Li-Grining, M. Metzger, K.M. Champion, and L. Sardin. 2008. "Improving preschool classroom processes: Preliminary findings from a randomized trial implemented in Head Start settings." _Early Childhood Research Quarterly_ 23 (1): 10-26.

- Rossin-Slater, M., and M. Wust. 2020. "What is the Added Value of Preschool for Poor Children? Long-Term and Intergenerational Impacts and Interactions with an Infant Health Intervention." _American Economic Journal: Applied Economics_ 12 (3): 255-86.

- Spier, E., K. Kamto, A. Molotsky, A. Rahman, N. Hossain, Z. Nahar, and H. and Khondker. 2020. "Bangladesh Early Years Preschool Program Impact Evaluation."

- Watts, T.W., J. Gandhi, D.A. Ibrahim, M.D. Masucci, and C.C. Raver. 2018. "The Chicago School Readiness Project: Examining the long-term impacts of an early childhood intervention." _PloS One_ 13 (7): e0200144.

- Weiland, C., and H. Yoshikawa. 2013. "Impacts of a prekindergarten program on children's mathematics, language, literacy, executive function, and emotional skills." _Child Development_ 84 (6): 2112-2130.

- Wolf, S. 2019. "Year 3 follow-up of the ‘Quality Preschool for Ghana’interventions on child development." _Developmental Psychology_ 55 (12): 2587.

- Wolf, S., and M.E. Peele. 2019. "Examining sustained impacts of two teacher professional development programs on professional well-being and classroom practices." _Teaching and Teacher Education_ 86: 102873.

- Wolf, S., J.L. Aber, J.R. Behrman, and E. and Tsinigo. 2019a. "Experimental impacts of the "Quality Preschool for Ghana” interventions on teacher professional well-being, classroom quality,