rafmacalaba/data-use-mentions-extended huggingface dataset:
information of both a general and a specific nature. The state government data was provided by the Deutsche Strassen Liga, a non-governmental institute. 22 The local government data was collected from the yearly Finanz Bericht and from interviews with road experts and officials in seven states. In addition, technical experts in Germany were contacted and interviewed to obtain the necessary information. Tables 3 and 4 display the information contained in the panel data set. Germany was selected as a case study because it has a high level of decentralized administration and construction and a low level of decentralized maintenance, in a fiscal sense.

# _The_ **_Impact_** _of Fiscal_ **_and Functional Decentralizationfrom Cross-Country Data_**

We use the double cost approach and hidden level of effort framework to measure the impact of fiscal decentralization on road provision using the cross-country panel. We estimate the four models defined in the last section, testing the various hypotheses postulated in the theory section. The estimation results are presented sequentially by model and comparisons of findings are done cumulatively across models.

# Model 1: The Independent Impact of Decentralization on Resource Costs.

The independent impact of decentralization on resource costs from the crosscountry panel is summarized in Table 5a while the impact of the control variables is presented in Table 5b. We find that after controlling for country-specific effects, income as measured by per capita GNP, and time, increasing the level of decentralization has a significant impact on resource costs. The impact of decentralization varies depending on the type of road function.

**Table 5a: Independent Impact of Decentralization on** Resource Costs

||Partial Effects|of Functional D|ecentralization|Total Effect of|
|---|---|---|---|---|
|Variable|Construction|Maintenance|Administration|Decentralization|
|fiscal|4.33|-<br>.63|0.44|9|
|decentralization|(0.74)|.0)|(1 .3_5)
Source: The World Bank TPP Database, 2016

# **Professional Services**

TPP countries have not liberalized the professional services sector beyond existing levels of openness and most countries commitments under the TPP reflect the level of openness in their existing PTAs. The exceptions are Malaysia and Singapore’s commitments on cross-border trade in accounting and auditing services that go slightly beyond their applied policies. Under Malaysia’s applied policy, auditing services cannot be provided cross-border but the TPP does not mention this restriction in the non-conforming measure list. In Singapore, local presence was required for the cross-border supply of accounting and auditing services but the TPP does not specify this restriction.

# **Figure 6: STRI for Professional services - Doha Offers, ‘Best PTA’, TPP Commitments and Applied Policy of 2015**

<!-- Start of picture text --> Professional: Doha, PTA, TPP and applied policy<br>BRN MYS CHL SGP MEX CAN VNM USA PER JPN AUS NZL<br>Doha PTA<br>TPP Policy '15<br>Note: Absense of a bar means there are no restrictions (STRI score is zero)<br>100<br>75<br>50<br>25<br>Services trade restrictiveness index<br>0<br><!-- End of picture text --> Source: The World Bank TPP Database, 2016

# **Temporary Entry of Business Persons**

As noted above, TPP commitments in Chapter 12 on the Temporary Entry for Business Persons cover not just business visitors (who do not actually provide services), but also installers and servicers, contractual service suppliers, independent executives and intra-corporate transferees. The US did not make any specific commitment in this area, while the other 11 TPP Parties agreed 18
FGDs, HE operators reported that they did not apply for credit in part because they were not confident about their ability to repay the loan. This finding was corroborated by the results of the FinScope 2009 survey, which show that among the majority of HEs who have never applied for a loan (87 percent), more than a third did not do so out of fear of not having enough money to repay the loan, while 17 percent said they actually did not have enough money. Taken together, these two groups constitute a little more than half of all HEs who did not apply for a loan, implying that their underlying problem is poor cash flow. Another 20 percent did not seek credit because of tough loan conditions (Table A1.16). HEs are therefore subjected to a vicious circle. Their high credit risk associated with their weak business performance makes it difficult for them to access bank credit to grow their business.

1. Even when microcredit companies (such as PRIDE or FINCA) and NGOs (such as VICOBA/DUNDULIZA) manage risk by lending to groups of HEs, the interest rate they charge is high. This is due not only to the high unit costs of providing credit to small borrowers, but also to high risk of default. Some lending companies charge as high as 40 to 100 percent interest per year along with short repayment periods. Weaknesses in the business and regulatory environment of the microfinance sector have constrained their effectiveness in addressing this

25
Policy Research Working Paper 9950

# **Abstract**

Sub-Saharan Africa hosts a large proportion of the world’s refugees, raising concerns about the consequences of hosting refugees. This paper focuses on Uganda, which is the largest refugee hosting country in Africa and is praised for its progressive refugee policy. The paper analyzes the effects of hosting refugees, relying on longitudinal data and an instrumental variable approach. The results indicate that Ugandan households benefit from living close to the refugee settlements. In contrast with the existing literature, the analysis finds that those initially involved in subsistence agriculture benefit the most. The effect seems to be driven by the few households able to move from subsistence agriculture to commercial farming and to some extent, to wage employment.

This paper is a product of the Social Protection and Jobs 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 MarkMarvin.Kadigo@uantwerpen.be, o.diallo@kit.nl, and jean-francois.maystadt@uclouvain.be.

_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
*32%**|**6%**|**16%**|
|IntergenerationalCorrelations(IGC)|**9%**|**4%**|**2%**|**7%**|
|**20-69 Year Age group**|||||
|Intergenerational Regression Coeff. (IGRC)|**15%**|**18%**|**6%**|**7%**|
|Intergenerational Correlations(IGC)|**6%**|**6%**|**2%**|**4%**|
|**13-50 Year Age group**|||||
|Intergenerational Regression Coeff. (IGRC)|**30%**|**46%**|**7%**|**22%**|
|Intergenerational Correlations(IGC)|**9%**|**11%**|**2%**|**10%**|

NOTE: (1) Bias is defined as [(Estimate from Full Sample – Estimate from Coresident Sample) *100] / Estimate from Coresident Sample (2) All of the Bias Estimates are Significant at the 5 Percent or Lower Level
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) and their outcomes have been quite detailed. However, it is unclear as to what extent the results between financial institutions are totally comparable. The possibility that authorities can perform the impact studies themselves (top-down approach) should not be discarded as a means to obtaining a readily and consistent, although perhaps rough, estimate of the impact of Basel III.

Banks typically report to PCRs their borrowers risk classification, produced either by the rules issued by the central bank or bank superintendency, or by their own rating system. If further basic information is available such as the type of borrower and credit, outstanding debt, residual maturity, type of mitigation securing each credit, simulating the impact of adopting Basel III is straightforward.<sup>29</sup>

> 28 Exposures that under Basel I carry an 8% capital requirement, under the IRB approach in Pillar 1 may experience dramatic shifts in their capital charge. This situation may tilt the playing field between Basel I and Basel III banks by shifting the incentives to assign capital to different types of credits. Bank regulators should carefully assess the effect on competition in the credit market and on the availability of credit.

> 29 Bank of Spain conducted several impact assessment exercises with its PCR information. Saurina and Trucharte (2004) analyze the impact of Basel II on lending to SMEs, while Saurina and Trucharte (2007) assess the effect procyclicality in mortgage portfolios. Repullo, Saurina and Trucharte (2009) analyze the procyclicality of Point-in-Time (PIT) and Through-the-Cycle (TTC) rating systems. A study on the stability of TTC ratings systems with PCR data of the Central Bank of Argentina can be found in Valles (2006).

11
growth rate of around 7 percent would be required to achieve SDG target 3.2 of doubling labor productivity within about 10 years. We find an additional month of recall length is associated with a 2 to 3 percent increase in reported output per unit of labor. What this shows is that the recall effect is likely to introduce an amount of variability that makes tracking progress towards achieving SDG targets and CAADP goals challenging and sensitive to the survey design choices that affect the length of recall. Policy and investment priorities based on these indicators risk being ineffective or misguided. Improving data quality is critical to minimize this risk.

The results lend support to ongoing efforts to mainstream more objective ‘gold standard’ measures of key variables into the design and implementation of surveys. The use of GPS devices to measure the area of agricultural plots is already considered best practice and incorporated into many surveys concerned with agricultural productivity and land use. In the field of production measurement, the practice of crop cutting is used in many national production estimations and other surveys, and our findings offer strong reasons for doing so systematically. Finally, when it comes to accurately measuring labor and fertilizer input, as well as counting all plots used in agricultural production, the use of diaries appears worth exploring.

One strategy to improve agricultural data reliability by shortening recall periods and recall length variation in household and farm surveys is to field two visits, one in the post-planting and one in the post-harvest period, rather than just one. While this strategy has cost implications, as field teams need to visit farms twice rather just once, it has the additional advantage of providing countries with more frequent and timely data on planting in the ongoing agricultural season. Another avenue to explore is the use of higher-

> 14 CAADP Indicator 2.1. _Increased agriculture production and productivity_ contains the following sub-indicators: 2.1.1 _Agriculture value added_ ; 2.1.2 _Agriculture production index_ ; 2.1.3 _Agriculture value added per agricultural worker_ ; 2.1.
employed. Upper and lower bound estimates sandwich true mobility confidence interval as before.

# _5.4. Alternative Specifications_

We also perform numerous empirical exercises to test the robustness of the findings to the explanatory variables used in the underlying models.

# _5.4.1. Actual Variables from Panel vs. those Created Using Cross Sections_

Columns four and nine of table 2c present estimates of mobility in Peru based on underlying models of consumption that include retrospective asset ownership as regressors (derived from questions in the cross sectional data on length of ownership of specific assets). In the case of Lanjouw et al. (2011), the authors force cross-sectional information to be time-invariant and retrospective by inserting the panel survey value of variables from the first round into the second round.

To test how well our “constructed” retrospective variables are, we force variables to be retrospective as in Lanjouw et al. (2011) and compare them with those in table 2c. Panel A of table 5 shows these results. Once again, the methodology is robust to the use of actual data; upper and lower bound estimates sandwich true mobility confidence interval and results are similar to those in table 2c. These results have important implications since they suggest that constructing retrospective variables should be done whenever they are available in surveys.<sup>8</sup>

# _5.4.2. Place of Residence_

Columns three and eight of table 2c shows estimates of mobility in Peru based on a consumption model that includes department of birth as regressor, as well as their interactions with household time invariant characteristics. Arguably, department of birth is of great value since it is time-

> 8 We also do a simple test of significance between the 6 asset variables we use in the analysis to test whether the panel values from the first round are not statistically different from those constructed using the information in round two. We find no significant difference for 5 out of the 6 variables.

17
the death rates during the Great Chinese Famine ranged from 5.8‰ to 33.8‰ with a mean death rate of 13.4‰ and a standard deviation of 5.8‰.

# **4.3 Factions, Local Accountability and Annual Growth**

We first compare the annual growth rates of real agriculture and industrial output per capita (also referred to as Gross Value of Output per Capita, or GVO per capita, henceforth) in counties led by YRD-affiliated cadres and those led by FA3-affiliated cadres. We also compare the annual growth rates in counties with local guerrilla presence prior to 1948 and those without guerrilla presence. We use the GDP deflator to compute the real growth rates. We have comprehensive data for all counties covered by our study from 1952 to 1998. To take into account important structural changes after the reform starting in 1978, we present the above comparisons both for the whole study period of 1952-1998 and only the post-reform period of 1978-1998.

Figure 2 plots the estimated kernel density distributions of the annual growth rates of real agriculture and industrial real output per capita by factions (FA3 vs. YRD, the top panel) or by local accountability as proxied by guerrilla presence (GuerrillaYes vs. GuerrillaNo, the bottom panel). The growth rates for the whole period of 1952-1998 were plotted in the left panel and those for the post-reform period of 1978-1998 were plotted in the right panel. The two graphs in the top panel show that the distribution of the growth rates among counties led by YRD-affiliated cadres is more heavily weighted on higher values than those in the counties led by FA3-affiliated controlling the length of seashore within the county. Again, it is never significant; thus we exclude it.

18
financial private sector. Because under financial liberalization transactions take place both domestically and abroad, we also evaluate the use of foreign capital markets. Second, we characterize which firms obtain financing from capital markets. Third, we analyze whether the use of capital market financing is associated with changes in firm performance around the capital raising activity. Fourth, we study the implications of the changes in firm size and growth for the firm size distribution (FSD) of listed firms.

To conduct the analysis, we assemble a unique and comprehensive data set on domestic and international capital raising activity and performance by Chinese and Indian firms. We particularly focus on the recurrent use of equity and bond markets among publicly listed firms (after their Initial Public Offering or IPO).<sup>5</sup> To do so, we compile transaction-level information on new capital raising issues of common and preferred equity from 1990 to 2011 and on corporate bond issues from 2000 to 2011 from Thomson Reuters’ Security Data Corporation (SDC) Platinum database. We then match the SDC Platinum data on the use of capital markets with the Bureau van Dijk Orbis data on annual firm-level balance sheet information for publicly listed companies from 2003 to 2011.<sup>6</sup> Our matched data set comprises 2,458 firms from China and 4,305 firms from India, out of which 1,915 and 3,428 firms, respectively, did not have any equity or bond issues between 2003 and 2011.

Two main broad features emerge from our analysis. First, our results suggest that the expansion of financing to the private sector in China and India has been much more subdued than what the aggregate numbers suggest. Although capital raising activity in equity and bond markets expanded substantially in 2005-2010, it remained small as a percentage of GDP.

> 5 Our focus on publicly listed firms provides us with a more homogeneous group of firms that, vis-à-vis non-listed firms, are large, have already met the costly listing requirements, and are formal corporations that
contrast, test for incentive effects associated with the introduction of the U.S. Millennium Challenge Account (MCA), which makes recipients eligible for its aid only if they are below a certain income threshold and above specified thresholds on a set of policy measures. Ohler,<sup> ̈</sup> Nunnenkamp, and Dreher (2012) focus on one key measure – an index of corruption – and report improvements in scores for countries and periods in a plausible treatment group relative to a plausible control group. This finding is rather surprising, however, given the short period of time covered by their analysis and the small amounts of aid commitments and disbursements by the MCA. Here, we use the World Bank’s “Country Policy and Institutional Assessment” (CPIA) index as our policy measure, which includes corruption as one sub-component. In addition, we show that policy-selectivity of aid started to increase quite substantially in the early 1990s, which corresponds to the end of the sample period used in Alesina and Weder (2002).

Our theoretical model is closely related to Annen and Knack (2018), who analyze a 2-donor-2recipient setup. Here, we look at a 1-donor- _n_ -recipient setup to focus more on the incentive effects the number of recipients has on the competition for aid. Also, we extend the framework by introducing an incentive alignment parameter between the donor and recipients, to see how it affects the incentive effect of policy-selective aid.

The remainder of the paper is structured as follows: Section 2 documents the policy selectivity of donors since 1985 as the key fact our paper builds on. Section 3 introduces the theoretical model. Section 4 uses the insights generated by the model to empirically test the impact of policy-selectivity on policies. Section 5 concludes.

# **2 Policy Selectivity of Foreign Aid**

The World Bank’s CPIA assesses the quality of countries’ present policies and institutions on a yearly basis for IDA and IBRD-eligible countries. Ratings for IDA but not IBRD countries are publicly
Policy Research Working Paper 8883

# **Abstract**

Improving the livelihoods of poor households and transitioning more women back to the labor force is a major challenge in South Asia. Self-employment promoted through women’s groups has often been cited as a promising intervention towards this end. However, the evidence on the impact of such programs on household income and labor outcomes is limited, especially for government programs like the National Rural Livelihoods Mission in India. This study aims to provide empirical evidence on the welfare impacts of an “intensive approach” adopted under this program. The data for the study come from 4,316 household surveys in 727 villages. The study uses matching methods with the population and socioeconomic census, as well as an instrumental variable approach to construct a retrospective control group. The analysis finds that the program has been able to achieve its primary objective of improving livelihoods by transitioning more women into work. The program has also expanded access to credit, increased the proportion of savings, and reduced interest rates on credit for rural households. This is the first study to estimate the annual income effects of a government-run rural livelihoods program in India, and it shows significant increases in median income across the sample. The results for 30th, 40th, and 75th percentiles are also large and significant. However, the study did not find significant average treatment effects for income. Contrary to previous studies, this study finds weaker impacts on assets, except for livestock.

This paper is a product of the Agriculture 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 agupta20@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