rafmacalaba/datause-encoder-data huggingface dataset:
||(0.4081)|(0.6600)|(1.1238)|
|---|---|---|---|
|**Observations**|307|136|94|
|**Peru:**||||
|**Management score**|‐0.0908|‐0.0584|1.3459**|
||(0.3032)|(0.6178)|(0.5818)|
|**Observations**|818|313|205|
|**Uruguay: **||||
|**Management score**|1.1181**|1.5504**|2.1498**|
||(0.4724)|(0.7493)|(0.9753)|
|**Observations**|263|100|67|

Notes: Standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1. Survey weights are used in all regressions. All regressions control for establishment characteristics.

In addition to looking at difference across size and country, it is interesting to consider what other factors may impact an establishment’s ability to benefit from improved management practices. **Error! Reference source not found.** Table 12 below shows that the premia associated with improved management differs by the degree of technological or knowledge intensity of the sector in which the establishment operates.<sup>6</sup> The results show no significant benefit from improved management practices in low‐tech sectors, while in medium and high‐tech sectors there is a positive and significant relationship between improved management and labor productivity. Considering total factor productivity, it appears that only establishments operating in high‐tech sectors benefit from improved management practices, although this result is based on a small sample size (only 39 establishments).

Table 12: Management and productivity, results by degree of technological / knowledge intensity

||**Y =**<br>|**Laborproduct**<br>|**ivity**<br>|**Y = To**<br>|**tal factorprod**<br>|**uctivity**<br>|
|---|---|---|---|---|---|---|
||Low tech|Med tech|High tech|Low tech|Med tech|High tech|
|**Management score**|0.2887|1.0963***|2.2762**|‐0.0544|0.1696|2.6269***|
||(0.2483)|(0.2843)|(1.0712)|(0.2061)|(0.3133)|(0.4846)|
|**Log size**|0.1200***|0.1564***|0.1506|0.1601***|0.0400|‐0.0747|
||(0.0353)|(0.0505)|(0.1636)|(0.0428)|(0.0461)|(0.1023)|
|**Age **|0.0002|0.0006|‐0.0129|‐0.0061**|0.0072*|‐0.0219***|
||(0.0023)|(0.0030)|(0.0095)|(0.0024)|(0.0038)|(0.0061)|
|**Foreign owned**|0.0064***|0.0037|0.0021|0.0005|‐0.0001|0.0001|
||(0.0019)|(0.0024)|(0.0077)|(0.0017)|(0.0022)|(0.0034)|
|**Multi‐establishment**|‐0.1262|0.1614|‐0.2686|‐0.2381*|‐0.0483|0.7363*|
||(0.1033)|(0.1658)|(0.5338)|(0.1339)|(0.2055)|(0.3938)|
|**Exporter**|0.0086***|0.0037**|‐0.0062|‐0.0008|0.0023|0.0040|
||(0.0026)|(0.0015)|(0.0042)|(0.0012)|(0.0015)|(0.0032)|

6 Sectors are classified as technologically or knowledge intensive sectors in accordance with the definition used by Eurostat, which is based on the ratio, at the sector level, of expenditure on research and development (R&D) to value added. For further details see https://ec.europa.eu/eurostat/statistics‐explained/index.php/Glossary:High‐ <u>tech_classification_of_manufacturing_industries, and https://ec.europa.eu/eurostat/statistics‐</u> explained/index.php/Glossary:Knowledge‐intensive_services_(KIS).

24
Opponents of the tariff cum subsidy policy claimed that it is doomed to fail because: (i) producers in Africa arc slow to adjust to a change in market signals (ii) the short run export supply elasticity is very small since African exporters cannot compete and capture international markets due to their high labor cost compared to their competitors and to the protectionist policies of the developed countries (iii) the export subsidies will lead to a comparable increase in domestic prices, leaving unaltered the relative profitability of exporting (iv) the import surcharges will not raise enough revenue to finance the export subsidies, implying a heavy fiscal burden on other revenue sources. The expected long run nonsustainability of this deficit will undermine from the beginning the credibility of the program and will discourage firms from responding to it.

These views have not been based on extensive empirical evidence, as evidence on export and output supply response is even more scarce for African countries than it is for other developing countries. One of the few studies is by Balassa (1987) who presents results suggesting that the response of exports of goods and agricultural products to price changes is actually greater in Sub-Saharan African countries than in other developing countries. (for evidence on other developing countries see, for example, Balassa et al 1986; Nogues 1989; Milanovic 1986; Artus and Rosa 1978; Goldstein and Khan 197&; Bauman and Braga 1988).

The objective of this paper is to address the first three issues (i-iii) above and to provide empirical evidence on export and output supply responses that could inform policy discussions on the tariff cum subsidy scheme introduced in C6te d'Ivoire in 1986. We base the empirical work on data from two sources for the six years that preceded the implementation of the program (1980-85). Information on sector level output, exports, domestic sales, capital, and variable input use is obtained by aggregating information from individual firm-level panel data obtained from the £anque des Donnees Financieres. The individual data was aggregated because export, import, domestic output, and input price indices obtained from the Ministere du Plan et de l'Industrie are available only at the sectoral (3 digit) level.

The paper .nodels the short-run response of firms to exogenous changes in export and import prices, taking into account the possibility that firms may sell to both domestic and foreign markets. In such a framework, firms may alter sales in response to the relative profitability of the two markets. The net output response depends on the response in both markets. In world markets, Ivorian industries are assumed to be price takers. In the domestic market, even if individual firms face exogenous pric-s, the

- 2 -
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Table 4b: Detailed Oaxaca decomposition of change in the 8<sup>th</sup> <u>grade Science score at the Mean</u>

|Mean prediction for 2003: 262.6<br>Meanprediction for 2007: 311.5|**Characteristics**|**Coefficients**|**Total Change **|
|---|---|---|---|
|**Total change**|**11.71**<br>**(7.4)**|**37.13**<br>**(18.2)**|**48.83**<br>**(24.5)**|
|**Characteristics component**||||
|Student and household characteristics||||
|Age|-1.22|1.43|0.21|
|Gender of student|-0.03|-0.34|-0.37|
|Speaks/not speak test language at home|0.00|1.12|1.12|
|Calculator at home|-0.12|-0.12|-0.24|
|Desk at home|-0.01|-1.61|-1.62|
|Works/Not in paid job|2.87|0.00|2.87|
|Homework time|1.66|1.95|3.61|
|Highest education of parent|-0.67|-2.04|-2.71|
|Both parents born/not born in country|0.52|-5.62|-5.10|
|Books at home|0.11|0.01|0.12|
|**Total**|**3.11**|**-5.22**|**-2.11**|
|School characteristics||||
|Total enrolment, grade 8|3.95|-9.03|-5.08|
|Community size|-0.62|-1.21|-1.83|
|Proportion of disadvantaged students|-0.25|3.05|2.80|
|Ability grouping yes/no|-0.54|2.62|2.08|
|Remedial lesson in Math Yes/no|-0.20|-1.12|-1.32|
|Severe absenteeism in school yes/no|0.90|5.13|6.03|
|Shortage of buildings yeas/no|0.50|-0.17|0.33|
|Shortage of teachers yeas/no|-0.01|0.38|0.37|
|Index of good attendance|-1.38|-1.04|-2.42|
|<br>**Total**|**2.35**|**-1.39**|**0.96**|
|Teacher characteristics||||
|Teacher age|0.61|-2.94|-2.33|
|Teacher gender|0.55|1.04|1.59|
|Teacher years of experience|0.03|-14.51|-14.48|
|Teacher education|0.66|-4.64|-3.98|
|Teacher certificate yes/no|1.41|3.00|4.41|
|Teacher feels safe/not safe|0.11|6.53|6.64|
|Teacher satisfaction|-0.39|2.48|2.09|
|Pay incentives for teachers yes/no|2.62|-8.16|-5.54|
|<br>**Total**|**5.6**|**-17.2**|**-11.6**|
|**Constant**|**-**|**60.95**|**60.95**|
|**N**||11,892||
|**2003:**||5,100||
|**2007:**||6,792||

z-values in parentheses.

23
interpretation of the land-related questions. This cognitive interviewing exercise led to the refinement of the phrasing of certain questions to address both translation and respondent interpretation issues.

Summary statistics are reported in Table 2. In the sample as a whole, 73% of households are deemed agricultural households, as defined by the SDG 5.a.1 methodology. Households, on average, are composed of four individuals, three of whom are adults (that is, 18 years or older). T-tests between Arm 1 and the other three arms indicate no significant differences in the characteristics presented in Table 2, with the exception of the age of the household head, which differs slightly between Arm 1 and the other arms.

_Table 2. Summary Statistics, by Arm_

||Total|Arm 1|Arm 2|Arm 3|Arm 4|
|---|---|---|---|---|---|
|HH size|4.0|4.0|3.8|4.1|3.9|
|# of adults/HH|3.0|3.1|2.9|3.1|3.0|
|Female headed HH (%)|0.31|0.31|0.30|0.28|0.34|
|Head age (years)|60.2|58.2|60.4**|60.7**|61.3***|
|# parcels owned/used per HH|-|1.48|-|1.42|-|
|Agricultural HH (%)|0.73|0.75|0.70|0.74|0.71|
|Urban (%)|0.36|0.36|0.36|0.36|0.36|
|Marz distribution (%)||||||
|Ararat|0.34|0.34|0.34|0.34|0.34|
|Kotayk|0.33|0.33|0.33|0.33|0.33|
|Vayots Dzor|0.33|0.33|0.33|0.33|0.33|
|N(HHs)|1200|301|300|298|301|

_Note: Asterisks indicate the value is statistically different from the corresponding value for Arm 1 at the 1% (***), 5% (**), and (10% *) levels._

# **IV. Indicator Concepts, Definitions, and Methods**

One of the main challenges when measuring land rights or tenure security is the definition in itself, as well as its operationalization. The concepts of land rights and land tenure security vary depending on the context of the analysis, leading to the emergence of a set of proxies employed throughout the literature to address questions of land rights (Doss et al., 2015). For example, studies analyzing the relationship between land rights and productivity or income in agriculture have focused more on the _use_ right, which is associated with the individual who makes farming decisions and withdraws outputs from the land, usually denoted as the land manager (Bambio and Agha, 2018; Lawry et al., 2017; Asfaw and Maggio, 2018). On the other hand, literature investigating the role of land as collateral in credit markets or studying farmer reactions to the efforts of large-scale investors to consolidate land has generally focused on documented ownership, deriving from the land registration and the owner’s possession of official documents (Domeher and Abdulai, 2012; Zhang et al., 2020; Joel and Bergaly, 2020). Work by Hasanbasri et al. (2022) uses data from Ethiopia, Malawi, and Tanzania to illustrate the importance of measuring multiple dimensions of land tenure, as gender gaps can vary significantly by type of right. The following are commonly used concepts for the analysis of land rights, which may be used jointly or in isolation, depending on the objective of the analysis and the features of the land tenure context in which the analysis is being conducted: 7
18 less employment in non-tradables (NTR...) than the resource-rich NRXGDP countries or the DEINDU countries, which deindustrialized post-1980. NTR is a non-tradable sector corresponding in this analysis to domestic _Wholesale and retail trade_ . NTR2 also includes _Other services_ that sometimes correspond to domestic commerce-related activities not included for some countries in NTR. NTR3 additionally includes _Household services_ .

We find, if anything, more government workers (GOVT) in MFGSERV countries. However, differences are not significant when adding education and health (GOVT2). This result is not since structural were surprising adjustment programs implemented in NRXGDP and DEINDU countries in the 1990s. We see more natural resource (NRX) workers in both NRXGDP and DEINDU countries, but the differences are not significant. Yet, we find significantly more fuel & mining workers in NRXGDP countries (not shown). Finally, we find less construction (CONST) in NRXGDP and DEINDU countries.

**Informality.** Using the same eq. (10), we test whether urban informal employment differs depending on the mechanism of urbanization. Our sample includes 55 sample countries for which we know whether the worker earns a wage, is self-employed, or works without pay. As shown in Cols. (1)-(3) of Table 4, the share of wage workers is lower and the share of self-employed workers higher in both NRXGDP and DEINDU countries (relative to MFGSERV countries). However, due to the sample size, differences are not significant.<sup>22</sup>

We expand on this further by testing whether tradables – proxied by MFG, the largest sector of MFG+FIRE – and non-tradables – proxied by NTR (domestic wholesale and retail trade) – have higher informality rates, as measured by self-employment. As seen in Cols. (4)-(6) and (7)-(9) of Table 4, MFG is more informal in the urban areas of NRXGDP and DEINDU countries than in the urban areas of MFGSERV countries, but these differences are not significant. NTR, however, is significantly more informal in the urban areas of NRXGDP countries than in the urban areas of MFGSERV countries.

**City-level results.** We use the city-level residualized measure of _Production / Consumption City-ness_ (PCC) obtained in Section 1 to examine if the patterns obtained at the countryurban sector level are driven by larger and/or smaller cities. For 6,211 FUAs, indexed with _a_ , belonging to 59 sample countries, indexed with _c_ , we regress PCC c. 2000 on the country-level variables of interest – MFGSERV (2000), NRXGDP (mean 1960-2000) and

22Self-employed workers are almost always self-employed without employees.
countries? _Journal of Economic Perspectives_ , 24 (1), 203-224.

- Bruhn, M., Karlan, D. & Schoar, A. (2010). What Capital is Missing in Developing Countries? _American Economic Review: Papers & Proceedings_ , 100 (2), 629–33.

- de Mel, S, D., Mckenzie, J. & Woodruff, C. (2009). Measuring microenterprise profits: Must we ask how the sausage is made? _Journal of Development Economics_ , 88(1), 1931.

- Drexler, A., Fischer, G., & Schoar, A.S. (2010). Keeping it Simple: Financial Literacy and Rules of Thumb, CEPR. Discussion Papers, No 7994.

- Hall, B., & Khan, B. (2003). Adoption of new Technology. NBER Working Paper No. 9730. Ichinowski, C., Shaw, K. & Prennushi, G. (1997). The effects of human resource management practices on productivity: A study of steel finishing lines. _American Economic Review_ , 87 (3), 291-313.

- Iddrisu, A. (2007). Cluster-based industrial development: The case of Suame Magazine vehicle repairs and metal work cluster in Ghana. Ph.D. Dissertation, the National Graduate Institute for Policy Studies (GRIPS), Tokyo.

- Imbens, G. & Angrist, J.D. (1994). Identification and estimation of Local Average Treatment Effects. _Econometrica_ , 62 (2), 467-475.

- Karlan, D. & Valdivia, M. (2011). Teaching entrepreneur: Impact of business training on microfinance clients and institutions. _Review of Economics and Statistics_ , forthcoming.

- Kennedy, L. (1999). Cooperating for survival: Tannery pollution and joint action in the Palar Valley (India). _World Development_ , 27 (9), 1673-91.

- Lazear, E. P. (2000).  Performance Pay and Productivity. _American Economic Review_ , 90(5), 1346-61.

- McCormick, D. (1999). African enterprise clusters and industrialization. _World_

26
## **FIGURE 11: CURRENT SSN, ENERGY SUBSIDY, AND NEW SSN SPENDING*, %GDP**

<!-- Start of picture text --> 10.0%<br>8.8%<br>8.0%<br>6.0%<br>4.7%<br>4.0%<br>2.8%<br>2.0%<br>2.0% 2.0% 2.0%<br>1.8%<br>1.5% 1.5% 1.6%<br>1.2% 1.3% 1.1%<br>0.4% 0.8% 0.8% 0.7% 0.3%<br>0.0%<br>Sub-Saharan East Asia & Pacific Europe & Central Latin America & Middle East & South Asia<br>Africa Asia Caribbean North Africa<br>SSN/GDP %, current Energy Subs/ GDP, % New SSN % GDP<br><!-- End of picture text --> Source: Authors and Weigand and Grosh (2008), and IMF (2013) Note: * New SSN Spending assumes 50% of Energy Subsidies Reallocated to SSNs As this paper has shown, countries can reach the poverty reduction target of 50 percent through social protection by either increasing generosity or the efficiency of public expenditure. Having used different scenarios for efficiency, we have shown that many countries can achieve the poverty target. This is not the case for all countries, particularly Low Income and Lower Middle Income countries. In these countries, the budget for social protection likely needs to be increased, though importantly this often does not require increasing the overall public expenditure envelope and may be achieved through fiscal reallocation.

# **5. Conclusion**

In this paper we argue that social protection must be an integral part of the post-2015 MDG framework. While acknowledging that social protection could be conceived as a development goal in itself, we have followed an essentially instrumental perspective in our approach. The evidence from across the developing world is clear: social protection programs have resulted in (often significant) reductions in poverty –and their absence constitutes a potentially serious threat to efforts to end poverty. More generally, they can contribute to improving equity, reducing income inequality and enhancing opportunities along the income distribution.

22
34

# Table 3.1 Chang in Poverty Incidence (percentage)

|Country and period|Poor population in initial year|Poor 2oDulation in final vear|
|---|---|---|
|Pakistan (1962-84)|54|23|
|India (1972-83)|_54_|43|
|Thailand (1962-86)|59|26|
|Malaysia (1973-87)|37|15|
|Indonesia (1970-87)|_58_|17|

**Source:** World Bank, World Development Report 1990.

Table 3.2: Incidence of PovertS in Pakistan

||Head<br>count|Percentage<br>share<br>Moor|<br>Percentage<br>share<br>popultn.|Index'|Headcount|Percentage<br>share<br>poor|Percentag<br>share<br>popultn|e Index'|
|---|---|---|---|---|---|---|---|---|
|Overall|18.3|100.0|100.0|100|13.1|100.0|100.0|100|
|Rural|21.1|83.21|72.17|115|_15.5_|85.82|72.61|118|
|Urban<br>................................|11.1<br>................................|16.79<br>..................................................|27.68<br>..............................................|61<br>.............................|6.8<br>....................................|14.18|27.53|52|

' Percentage share of poor households divided by the category's share of total households.

Note: The poor in 1984/85 are defined to be those households whose incomes are below that required to meet expenditures of Rs. 150 per capita needed to consume 2,550 calories. The poverty line for 1987/88 is adjusted for the price increase.

Source: S.J. Malik, Poverty in Pakistan. July 1991 IFPRI, Washington, D.C.

Agriculual credit for productivity growth wouid in itself help alleviate rural pwerty by incsng rurl incomes and creating nonfain rural income opportunities. However, there remains a large group of the nual destitute in Pakisan who need credit to engage in sustainable income-generating activities. This group of the rurl poor **consts** about 20 percent of the rural population.
Policy Research Working Paper 8646

# **Abstract**

The production of export goods has become increasingly unbundled, and countries positioning to become more integrated in the global economy are increasingly looking toward global value chains. This paper uses the Organisation for Economic Co-operation and Development/ World Trade Organization’s Trade in Value Added Database to assess Brazil’s current integration in global value chains. It uses a structural gravity model estimated with parts and components to analyze the scope for Brazil to increase global value chain–related trade. One avenue to raise participation in global value chains is through (deeper) preferential trade agreements, and to this end the paper characterizes the level of integration of Brazil’s current preferential trade agreements. Brazil has witnessed high growth in total domestic value added embodied in gross exports since 1995, yet it exhibits lower international engagement in global value chains, but tends to be stronger as a seller than a buyer. Most of the participation on the selling side comes from indirect linkages with domestic input sectors, and services sectors have been important for growing the indirect value added in global value chain–oriented exports. A deep integration agenda focusing not only on border measures, but also on beyond-the-border measures, would help Brazil to maximize the benefits from participation in global value chains. Other than its natural partners, Brazil should integrate with countries where global value chains are taking place. New agreements signed by Brazil and Mercosur with other regional members such as the Pacific Alliance should also take into consideration provisions such as investment, competition policy, and intellectual property rights, which are demonstrated to be very important for integration in global value chains.

This paper is a product of the Macroeconomics, Trade and Investment 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/research. The authors may be contacted at nrocha@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 its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team