rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 5070

# **Abstract**

In rural Indonesia, around 60 percent of workers engage in agriculture and face regular climatic shocks that may threaten their crop production, household income, and human capital investments. Little is known about households’ ability to maintain consumption in response to these shocks. This paper uses both longitudinal and repeated cross-sectional data to examine the extent to which farm profits and household consumption are reduced by delayed monsoon onset, an important determinant of rice production in Indonesia. It also investigates whether poor households are more vulnerable to delayed onset. Overall, delayed onset has minor effects on rural households’ profit and consumption. For poor households, defined as those with average per capita consumption in the lowest quintile, delayed onset the previous year is associated with a 13 percent decline in per capita consumption. Most of this decline is due to an increase in household size, however, and delayed onset two years ago is positively correlated with consumption. The findings suggest that poor households experience greater volatility but no lasting reduction in consumption following delayed monsoon onset.

This paper—a product of the Poverty Reduction and Economic Management Division, East Asian and Pacific Region—is part of a larger effort in the region to understand the effects of climate shocks on households in developing countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dnewhouse@worldbank.org or mduarte@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
||(0.0467)|(0.0518)|(0.0402)|(0.260)|(0.0566)|(0.0546)|
|---|---|---|---|---|---|---|
|For_2004|0.143**|0.201**|0.200***|-0.00693|0.0887|0.216**|
||(0.0629)|(0.0885)|(0.0514)|(0.221)|(0.0762)|(0.0912)|
|For_2005|0.133*|0.153|0.203***|0.0120|0.0632|0.170|
||(0.0776)|(0.115)|(0.0601)|(0.178)|(0.0960)|(0.121)|
|For_2006|0.154*|0.169*|0.217***|0.00373|0.0841|0.180*|
||(0.0781)|(0.0999)|(0.0638)|(0.218)|(0.0949)|(0.104)|
|For_2007|0.163*|0.163*|0.227***|0.178|0.0860|0.180*|
||(0.0911)|(0.0922)|(0.0718)|(0.236)|(0.111)|(0.0957)|
|lnTariff|-0.0200|-0.0322*|-0.00861|-0.0332|-0.0241|-0.0321*|
||(0.0172)|(0.0177)|(0.0148)|(0.0431)|(0.0190)|(0.0179)|
|lnbwTariff|-0.0267|-0.00377|-0.0126|0.00929|-0.0334*|-0.00161|
||(0.0172)|(0.0283)|(0.0136)|(0.0711)|(0.0200)|(0.0284)|
|lnfwTariff|-0.00712|0.00314|-0.0150**|0.0910***|-0.00488|0.00220|
||(0.00780)|(0.00735)|(0.00711)|(0.0160)|(0.00795)|(0.00727)|
|Constant|1.740***|2.393***|1.927***|1.221***|1.682***|2.394***|
||(0.0561)|(0.0644)|(0.0511)|(0.144)|(0.0652)|(0.0656)|
|Observations|1,418,632|126,994|345,631|2,398|1,073,001|124,596|
|R-squared|0.190|0.083|0.212|0.274|0.175|0.082|

_Notes_ : We keep the same structure as in Table 6. In this table, we explore time effects of sector-level spillover variables on firms‘ productivity. We use year dummies to multiply _Horizontal_ , _Backward_ , and _Forward_ separately; therefore, we have 30 interactions. Hor_interact1 = Horizontal * time dummy (when year = 1998).

48
__________ (1994), "The Impact of Population Policies: Comment", Population and Development Review, 20(3), 616-620.

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Fink, G. (2007), "College Education and Fertility Outcomes," mimeo, Harvard School of Public Health.

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Jensen, S. E. H. and O. H. Jorgensen (2008), "Uncertain Demographics, Longevity Adjustment of the Retirement age and Intergenerational Risk-Sharing," in S. J. Alho, S. E. H. Jensen and J. Lassila (eds.), _Uncertain Demographics and Fiscal Sustainability_ , 239-257, Cambridge University Press.

Jorgensen, O. H. and S. E. H. Jensen (2009), "Labour Supply and Retirement Policy in an Overlapping Generations Model with Stochastic Fertility," Discussion paper on Business and Economics, 1/2009, Department of Business and Economics, University of Southern Denmark.

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20
-1 9-

Equation (1) states that the change in the external debt to GDP ratio can be traced to three factors: (i) the growth in the ratio due to the excess of the foreign real interest rate over the real growth of GDP _((r-g)d);_ (ii) te non-interest current account balance (v); and (iii) the capital loss on external debt due to real exchange rate depreciation ( A@) . The contribution of the three factors to the change in the external debt-GDP ratio is shown in Table 12. The main results are as follow:

# Table 12. Pakistan: Determinants of External Debt-GDP Ratio. 1973-1991 (%6)

||_Ad_|_(r-g)d _||Aed|
|---|---|---|---|---|
|1973-191|-28.4|-64.8|.40.3|_-39_|
|1981-1991|16.1|-26.8|-19.3|23.6|

Source: Own estimates.

- Between 1973 and 1981, Palistan experienced substantial non-interest current account deficits. By itself, this should have contributed sipificantly to raising the external debtGDP ratio. However, the ratio declined noticeably because the adverse implication of these deficits was more than offset by the contributions of a large negative external interest rate and the high GDP growth rate<sup>7</sup> . The appreciation of the real exchangc rate (see Graph 7) also contributed to reducing the external debt-GDP ratio by causing a capitl gain on the stock of real debt, although it tended to raise the ratio on the flow side by worsening the current balance.

- In sharp contrast to the earlier period, between 1981 and 1991, the external debt-GDP ratio increased noticeably, even though the level of non-interest current balance was on average less negative than during 1973-81 and the average' growth of GDP was somewhat higher than in the previous period. The external debt to GDP ratio increased partly because the foreign real interest rate turned positive and, as a result, the cushion provided by the large negative "dynamic debt component"-(r-g)d-was weakened in this penod. Furthermore, while the depreciation of the real exchange rate helped reduce the non-interest current deficits, it also had a substantial offsetting rising impact on the external debt-GDP ratio through its direct effect on capital losses on the stock of debt.

**T** he interest rate is defined as the average inteu rate and is derived as the rado of interest payments to total exteral debt. The main reason why average nominal inerest rates were so low in this period is because of the dominance of official concessional loans in the external debt portfolio.
registries and find that introduction of these registries increases access to bank finance in general by 8%. Importantly they show that smaller firms (5-19 employees) and younger firms benefit more from the registry than respectively larger and older firms. Campello and Larrain (2016) identify some of the mechanisms through which these collateral reforms lead to greater lending. They find that after reforms enlarging collateral menus were passed in a number of Eastern European countries to include movable assets (e.g. machinery and equipment) as collateral, firms in movable-intensive sectors borrowed more, invested more in fixed assets, hired more workers, and became more efficient and profitable.

Haselmann, Pistor, and Vig (2009) study both bankruptcy and collateral reforms in Eastern Europe and find that these reforms led to greater lending and that smaller borrowers benefit more than larger firms. While the bankruptcy reforms increase the likelihood that individual creditors can realize their claims against a debtor, the collateral reforms provide an orderly process for resolving claims after a debtor has become insolvent. The authors show that the collateral regime is of greater importance than a bankruptcy regime for lenders. Visaria (2009) studies the establishment of Debt Recovery Tribunals (DRTs) in India that empowered creditors in seizing assets of defaulting firms and finds that enforcement of lenders’ rights improved the repayment behavior of delinquent borrowers.

However, there is countervailing evidence on the effect of strengthening creditor rights by negatively affecting the demand side (e.g. Acharya and Subramian (2009), Acharya, Amihud and Litov (2011)). Vig (2013) studies the passage of a 16
# **1 Introduction**

Higher education can be a powerful source of social mobility and economic growth. Although bachelor’s programs attract about three quarters of higher education enrollment worldwide, their returns vary widely and are not necessarily the best option for all students.<sup>1</sup> Further, the recent COVID-19 pandemic has shown the urgent need for workforce upskilling and reskilling. Shorter and more practical than bachelor’s programs, short-cycle higher education programs (SCPs) are uniquely suited to these roles. SCPs are two- or three-years long and correspond to associate degrees in the US, where they are typically taught at community colleges.<sup>2</sup> They prepare students for the labor market, often with a strong occupational content. They can play a central role addressing to rapidly changing market needs, expanding higher education to nontraditional students, and providing lifelong learning opportunities.

Despite their promise, SCPs have some shortcomings. Crucially, student academic and labor market outcomes vary greatly among SCPs. This holds for multiple countries and after controlling for student and peer characteristics.<sup>3</sup> Taking program costs into account, net economic returns vary greatly as well and are negative for many SCPs. Whether program quality is measured by outcomes or returns (raw or adjusted by student characteristics), high- and low-quality programs clearly

> 1 For bachelor’s enrollment rates worldwide, see UNESCO (http://data.uis.unesco.org/). On the variation of returns to bachelor’s programs, see, for instance, Hoxby and Stange (2019) and Lovenheim and Smith (2022) for the US, and Ferreyra et al. (2017) for the developing world.

> 2 These programs have different names depending on the country. In this paper, we follow UNESCO’s nomenclature of short-cycle programs, corresponding to level-5 programs in the International Standard Classification of Education (ISCED).

> 3 See, for instance, Jepsen et al., 2014; Dadgar and Trimble, 2015; Stevens et al., 2019; Liu et al., 2015; Grosz, 2020, and Mountjoy, 2021 for the US; Aucejo et al. (2020) for the UK; and Ferreyra et al., 2021; Ferreyra et al, 2020 for Latin America and the Caribbean.

2
# **_Spousal disagreement_**

Table 1 showed us that the household is not unitary, and decision-making is relational. In what follows, we unpack spouses’ decision-making reports. As discussed above, recent studies have mostly focused on spousal accord or general disagreement when examining the relationship between intra-household decision-making and empowerment. However, looking at disagreement solely as a binary variable can cloud important differences, as women’s agency could vary substantially depending on whether disagreement assigns more or less power to the woman. That is, the direction of the disagreement might be more important for the measurement of agency than simply looking at spousal response discrepancy. Unpacking different disagreement scenarios may also provide greater understanding on why accounting for spouses’ responses weakens the association between women’s involvement in decision-making and proxies of their empowerment that we saw in Table 1.

**Table 2. Share of couples' responses (averaged across countries)**

|_Who u_|_sually makes_||_Wife’s response:_||
|---|---|---|---|---|
|_deci_|_sions about_||||
|_ma_|_king major_|Husband|Joint|Wife|
|_househ_|_old purchases?_||||
|_ponse:_|Wife|4.5%|5.1%|1.6%|
|_nd’s res_|Joint|13.6%|26.4%|5.0%|
|_Husba_|Husband|24.5%|15.8%|3.4%|

16
WPS3756

# Enforcement of Labor Regulation, Informal Labor, and Firm Performance

Rita Almeida ∗ World Bank Pedro Carneiro University College London, Institute for Fiscal Studies and Center for Microdata Methods and Practice

## **Abstract**

This paper investigates how enforcement of labor regulation affects the firm’s use of informal employment and its impact on firm performance. Using firm level data on informal employment and firm performance, and administrative data on enforcement of regulation at the city level, we show that in areas where law enforcement is stricter firms employ a smaller amount of informal employment. Furthermore, by reducing the firm’s access to unregulated labor, stricter enforcement also decreases average wages, productivity, and investment. Our results are robust to several specification changes, and to instrumenting enforcement with 1) measures of access of labor inspectors to firms and 2) measures of general law enforcement in the area where the firm is located.

Keywords: Informal Sector, LaborMarket Regulation, Labor Demand, Flexibility, Productivity.

JEL Classification codes: J3, J6, O17.

World Bank Policy Research Working Paper 3756, October 2005 _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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._ ∗ Corresponding author: Rita Almeida (ralmeida@worldbank.org). We thank the Brazilian Ministry of Labor for providing us the data on enforcement of labor regulation that we use in our paper and important information about the process of enforcement, especially Edgar Brandao, Sandra Brandao and Marcelo Campos. We thank George Clarke, Saul Estrin, Ana Fernandes, Mary Hallward-Driemeier, John Haltiwanger, Jennifer Hunt, Sara Lemos, Adriana Kugler, Stefano Scarpetta, Luis Serven, Rodrigo Soares and participants in several seminars for valuable suggestions. Carneiro thanks the hospitality of the Poverty Unit of the World Bank Research Group.
Policy Research Working Paper 8801

# **Abstract**

This paper presents a structural general equilibrium model to analyze the effects on trade, welfare, and gross domestic product of common transport infrastructure. Specifically, the model builds on the framework by Caliendo and Parro (2015)—a Ricardian model with sectoral linkages, trade in intermediate goods and sectoral heterogeneity—to allow for changes in trade costs due to improvements in transportation infrastructure, financed through domestic taxation, connecting multiple countries. The model highlights the trade impact of infrastructure investments through cross-border input-output linkages. This framework is then used to quantify the impact of the Belt and Road Initiative. Using new estimates on the effects on trade costs of transport infrastructure related to the initiative based on Geographic Information System analysis, the model shows that gross domestic product will increase by up to 3.4 percent for participating countries and by up to 2.9 percent for the world. Because trade gains are not commensurate with projected investments, some countries may experience a negative welfare effect due to the high cost of the infrastructure. The analysis also finds strong complementarity between infrastructure investment and trade policy reforms.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice and the Office of the Chief Economist, Middle East and North Africa Region. 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 fdesoyres@worldbank.org, amulabdic@worldbank.org, and mruta@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
|**HS**||||Year|||
|---|---|---|---|---|---|---|
|<br>**code**<br>|**_Type of products_**|2001|2002|2003|2004|2005|
|**2 digits**|||||||
|50||5.0|5.0|5.0|5.0|5.0|
|||_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|
|||82<br>|82<br>|80<br>|80<br>|80<br>|
|51|_WOOL ANIMAL HAIR_|14.6|14.6|14.7|14.7|14.7|
||_,_|_(1.4)_|_(1.4)_|_(1.2)_|_(1.2)_|_(1.2)_|
|||162|162|162|162|162|
|52|_COTTON_|11.2|11.2|11.2|11.2|11.2|
|||_(5.1)_|_(5.1)_|_(5.1)_|_(5.1)_|_(5.1)_|
|||43|43|43|43|43|
|53|_VEGETABLE TEXTILE_|7.4|7.4|7.4|7.4|7.4|
|||_(3.5)_|_(3.5)_|_(3.5)_|_(3.5)_|_(3.5)_|
|54|_MANMADE FILAMENTS_|89<br>10.3|89<br>10.3|89<br>10.3|89<br>10.3|89<br>10.3|
|||_(1.8)_|_(1.8)_|_(1.8)_|_(1.8)_|_(1.8)_|
|||170<br>|170<br>|170<br>|170<br>|170<br>|
|55|_MANMADE STAPLE FIBRE_|7.9|7.9|7.9|7.9|7.9|
|||_(2.5)_|_(2.5)_|_(2.5)_|_(2.5)_|_(2.5)_|
|||68<br>|68<br>|68<br>|68<br>|68<br>|
|56|_WADDING FELT_|14.9|8.8|8.8|9.0|8.9|
||_,_|_(48.7)_|_(5.2)_|_(5.0)_|_(5.3)_|_(5.0)_|
|||39<br>|39<br>|39<br>|39<br>|39<br>|
|57|_CARPETS_|21.2|23.8|23.0|21.2|20.1|
|||_(3.4)_|_(13.4)_|_(6.2)_|_(2.7)_|_(0.7)_|
|||56|56|56|56|56|
|58|_SPECIAL WOVEN_|20.0|20.0|20.0|20.0|20.0|
|||_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|
|||43|43|38|38|38|
|59|_TEXTILE FAB COATED_|6.6|7.2|8.3|7.2|7.2|
|||_(3.7)_|_(5.7)_|_(9.7)_|_(4.6)_|_(4.4)_|
|||65|65|65|65|65|
|60|_KNITTED OR CROCHETED_|10.0|10.0|10.0|10.0|10.0|
|||_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|_(0.0)_|
|||176|176|176|176|176|
|61||22.2|24.9|27.8|23.0|20.8|
||_ARTICLES OF APPAREL KNIT_|_(8.7)_|_(16.1)_|_(15.2)_|_(11.9)_|_(5.0)_|
|||204|204|204|204|204|
|62|_ARTICLES OF APPAREL_|24.3|25.8|29.4|21.6|20.8|
|||_(18.0)_|_(23.8)_|_(28.7)_|_(6.2)_|_(5.0)_|
||_OTHER TEXTILE ARTICLE_|94|94|94|94|94|

29
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