rafmacalaba/datause-encoder-data huggingface dataset:
22 investments in financial intermediaries. Thus, QLLY focuses on measuring longer-term liabilities - quasi-liquid liabilities: M3-Ml.

Since liquid and quasi-liquid liabilities that finance government deficits may not reflect the provision of efficient financial intermediary services (such as acquinrng information about firms, monitoring managers, and facilitating transactions and risk diversification), we also compute the variable PRIV/GDP. PRIV/GDP equals the ratio of domestic credit to private firms divided by GDP.<sup>9</sup> Table 11 indicates that Hong Kong, Japan, and Switzerland have well-developed financial system as measured by M3/GDP, QLLY, and PRIV/GDP. In contrast. Argentina, Brazil, Mexico, Colombia, and Nigeria had very underdeveloped financial systems as revealed by these three indicators over the 1986-1993 period.

A.2. **Bank development:** To measure the level of development of the banking system we use BY/GDP, which equals the ratio of the total claims of deposit money banks to GDP. The three countries with the largest BY/GDP variables are Switzerland, Luxembourg, and Japan. At the other extreme, Colombia, Nigeria, and Argentina had the lowest ratio of bank credit to GDP 9 Unfortunately, while the Intemational Financial Statistics classifies credit as "claims on the private sector," some of these claims in some countries include credit to public enterprises.
Table 5: long-term versus short-term bonds - OLS and Poisson

|Dependent variables:|log(Long bonds) <br>(1)|— log(Short bonds)<br>(2)|Long bonds <br>(3)|— Short bonds<br>(4)|
|---|---|---|---|---|
|log(<br>Migration )|0.1690**|0.071|O.161***|0.143**|
||(0.076)|(0.100)|(0.029)|(0.071)|
|log(Distance)|—0.471***|—0.800***|—0,329***|—0.145|
||(0.107)|(0.156)|(0,083)|(0.094)|
|N|541|Sl|1517|1517|
|L|ol|ol|32|32|
|B|85|85|92|92|
|Estimator|OLS|OLS|Poisson|Poisson|

In this table the dependent variable is investment in long-term bonds and short-term bonds. NV, and B denote number of observations, number of lending (investing) countries and number of borrowing (issuing) countries, respectively. Regressions are estimated by OLS and Poisson. Standard errors are clustered at the borrowing country level. All columns include country fixed effects, colonial link, language, legal origin and common border as additional controls. The data is described in section IT.

Table 6: Comparison between Developed and Developing countries - OLS and Poisson

|Dependent variables:|log(Loans)|Loans|
|---|---|---|
||(1)|(2)|
|logMigration;;|OA02="|Qoier|
||(0.049)|(0.041)|
|logMigration;; * (Developing Country);|0.045<br>(0.044)|0.145**"*<br>(0.039)|
|logDistance;;|<br>—0.837***|<br> —0.266***|
||(0.121)|(0.052)|
|Obs.|1,451|1,588|
|No. of Lending Countries|17|i|
|No. of Borrowing Countries|158|158|
|Obs.|1,451|1,588|
|Obs with Developed Borrowing Countries|427|431|
|Obs with Developing Borrowing Countries|1,024|1,157|
|No. of Lending Countries|17|17|
|No. of Borrowing Countries|158|158|
|Estimator|OLS|Poisson|

This table adds an interaction of migration with developing countries. N, L and B denote number of observations, number of lending (investing) countries and number of borrowing (issuing) countries, respectively. Regressions are estimated by OLS and Poisson. Standard errors are clustered at the borrowing country level. All columns include country fixed effects, colonial link, language, legal origin and common border as additional controls. The data is described in section II.
Table 1: Village Heads’ Adherence to Regulated Procedures (Control Group)

|Mean in Control Group|N|
|---|---|
|Consultation of resource management council<br>0.389|126|
|Consultation of women’s council<br>0.226|124|
|Proportion of female dare members<br>0.262|125|
|Access to records<br>0.645|124|
|Nopayments<br>0.336|119|

Table reports means of each variable in the villages that did not receive any training in year 1.

In table 2, we observe that the amount of bias in favor of the village head’s co-partisans is actually relatively small (and statistically insignificant) in the case of food aid distribution – people who said they had different political views from their village head were only five percentage points less likely to receive food aid than people who said they had the same political views as their village head.<sup>12</sup> However, we find substantial perceived bias in the case of court decisions; people with different political views from their village head were 20 percentage points less likely to believe that most of the village court’s decisions were fair and 8 percentage points less likely to take the most common local disputes – disputes over the destruction of crops by livestock – to them for resolution.

Thus, the widespread bias in village heads’ decision-making gives many citizens grievances against them. The question of how to reform village-level governance is tricky because of the low potential for top-down reform and the weak mechanisms in place for achieving change from the bottom up. Instead, the intervention described in the next section draws on the tradition of senior community members providing advice to village heads as a potential mechanism of reform.

way through surveying, so we do not have data on this question for one-third of respondents. Fortunately, because the survey was proceeding geographically and we randomized by geographic blocks, the sample is still well balanced across experimental arms. In table 8 of the appendix, we consider how the villages for which we have political data differ from the villages for which we do not.

> 12Interestingly, these results are not simply the result of the village head’s personal biases being overwhelmed by biases against opposition supporters. There is even less evidence that supporters of the ruling party are favored in the distribution of food aid in our study villages, as indicated in the results in table 2 of the appendix. Much of the food aid in these villages comes from international organizations, which may explain the limited bias.

13
<!-- Start of picture text --> 100%<br>80% -_<br>60%- 1<br>40% -7<br>2%<br>0%.- 111111<br>Cu m C .) 0 u Cu to to Cu Cu Cu C C £ C u u C<br>C ~~ ~~ ~ *E Cu E .E. ~~ j ~ ° .~ E 2<br>C S c 0 E X<br>On N<br><!-- End of picture text --> Figure 1: Cellular subscribers per main fixed line. Data Source: Intemational Telecommunications Union (2001).

The macroeconomic and political data used to control for factors that might affect the overall level of corruption in the countries in the sample are taken from a variety of sources including World Bank (2001), Beck _et al._ (2001), and Freedom House (2000). Table 1 and Table 2 provide sources, brief descriptions and summary statistics for the main variables used in this analysis.

12
Table 2: Estimated average treatment effect on number of fire occurrences excluding the forest fringe

|Month|Year|(1)<br>No thresh.|(2)<br>Fire occurrences<br>1 km thresh.|(3)<br>2 km thresh.|
|---|---|---|---|---|
||2014|–0.073|–0.053|–0.010|
|||[0.284]|[0.285]|[0.971]|
||2015|–0.093***|–0.174***|–0.081|
|||[0.002]|[0.001]|[0.116]|
||2016|–0.126***|–0.158**|–0.106|
|Nov||[0.000]|[0.023]|[0.139]|
|.|2017|–0.026***|–0.025|–0.039|
|||[0.003]|[0.424]|[0.474]|
||2018|–0.054|–0.118|–0.060|
|||[0.459]|[0.318]|[0.698]|
||2019|0.023|–0.011|0.048|
|||[0.212]|[0.276]|[0.955]|

_Note_ : Estimates are based on the synthetic control method using forest-month level data. We use fires with 30% or better confidence to construct the outcomes. Treatment start from October 2014. P-values from the placebo analyses, in which treatment effects are standardized by pre-treatment RMSPE, are in brackets. Average fire spread is measured in km<sup>2</sup> . *** p _<_ .01, ** p _<_ .05, * p _<_ .1 of grid cells affected by fire in the post-harvesting month in the period 2015-2017 as it was in reducing overall forest fire occurrences. Indeed, the percentage-point reduction in the share of grid cells affected by fire in the 2015-2017 November months ranged between 8 _._ 2% and 10 _._ 1%. From Columns (2) and (3) we can infer that the main reason why the intervention was effective was that it resulted in a better containment of forest fires. As shown in Column (2), fewer fires were started throughout the post-intervention period, but these reductions are not significant in any of the post-intervention years except for 2016. Column (3), however, shows that the intervention resulted in a reduced spread of forest fires over neighboring grid cells in both 2016 and 2017: the 2 _._ 10 km<sup>2</sup> and 1 _._ 83 km<sup>2</sup> decreases in the size of fire events translate into a 38% and 29% decrease, respectively. We thus find that the reductions documented in Table 1 are more likely the result of improved forest fire containment than of a sizeable and long-lasting reduction in the number of fires started. Also note, however, that while the point estimate with respect to the number of fires started in 2018 was negative and sizeable (see Column (2)), this effect is not statistically significant, and we observe a sizeable _increase_ in the 24
# **ELECTORAL ACCOUNTABILITY AND LOCAL GOVERNMENT SPENDING IN INDONESIA**<sup>**1**</sup>

Emmanuel Skoufias<sup>*</sup> Ambar Narayan Basab Dasgupta Kai Kaiser THE WORLD BANK

## **JEL Classification Codes:** D7, H7,O2, R5

**Key Words:** Decentralization, District Budget and Expenditures, Direct Elections, Indonesia.

> 1 This paper represents a revised and updated version of an earlier paper by the same authors titled “Electoral Accountability, Fiscal Decentralization, and Service Delivery in Indonesia,” available as World Bank Policy Research Working Paper No. 5614, March 2011, http://go.worldbank.org/BWBRP91A50.  This version takes advantage of recently released district level revenue and expenditure data for the years 2001 to 2009, and as a consequence, the findings and conclusions differ from those in the earlier version based on only one year of post-election data.

> * _Corresponding Author_ : Emmanuel Skoufias, The World Bank, Mail Stop MC I4-405, 1818 H Street NW, Washington, DC 20433, USA. tel: (202)458-7539. fax: (202)522-3134. E-mail: eskoufias@worldbank.org

> _Acknowledgements:_ The authors are grateful to Sukmawah Yuningsih, Indira Maulani Hapsari, and Laura Maratou-Kolias for excellent research assistance, and to Wolfgang Fengler, William Wallace, Shubham Chaudhuri, Daan Pattinasarany, Bastian Zaini, and Cut Dian Agustina for supporting this work over the years. Stuti Khemani, Philip Keefer, and Benjamin Olken provided very useful comments in earlier versions of this paper. The findings, interpretations, and conclusions in this paper are entirely those of the authors and do not reflect the views of the World Bank.
-10-

# III. PUBLIC REVENUES AND EXPENDITURES

The fiscal policy in Cote d'Ivoire has been characterized bj wide fluctuations of revenues, expenditures and deficits. In order to put these in some perspective we will use the notions of structural levels of revenues and deficit, which are familiar in industrialized countries. In this section we first present a brief description of the sources of public revenues and a discussion of their structural level. The level of structural revenues will provide the basis for the computation of the structural surplus (or deficit). After this computation, we will consider how the composition and the drift of expenditures led to the fiscal deficit and the present crisis.

# 3.1 The Structural Level of Public Revenues

The structure of public revenues in Cote d'Ivoire similar to that of other Sub-Saharan countries2: The domestic sector which is formal and non agricultural is very small. Hence the domestic base for taxation is narrow, and most taxes are levied at the border or on the rural sector that sells the primary commodities (cocoa and coffee), to a marketing board. A description of the basic composition of revenues is essential for the understnading fo the fiscal policy since 1975.

The institutional rules of the CFA put severe restrictions on domestic borrowings by the government: the level of the domestic government debt cannot exceed 20 percent of the previous year's tax revenues. This creates an

> 2See the survey of Tanzi [19881.
in order to show the robustness of our results, we present them considering exchange rates in levels or in differences, or no exchange rate at all.

Besides asset returns, our empirical analysis also uses data on the bilateral current account between the U.S. and Japan, total wealth, national savings, national consumption, and GNP. The bilateral current account data is from the U.S. Bureau of Economic Analysis. We follow the methodology described in Kraay et al. (2005) to construct measures of total wealth. National savings, national consumption, and GNP are from IMF’s _International Financial Statistics._

# **4.3 VAR Estimation**

Our empirical results depend on the estimation of the system of equations (13). We thus report the estimations based on five different specifications of this VAR system.<sup>20</sup> Through the rest of the paper, we report results for all these specifications. We show that the expected asset returns obtained from these different estimations have similar dynamics. We will argue that our empirical analysis is robust to these different estimations. In other words, the portfolio allocations implied by these different VAR systems are similar in their composition, and thus lead to similar predictions for the bilateral current account between the U.S. and Japan.

In our theoretical model, we have assumed that investors from both countries have access to the same information set. They use the same model and know the current state of the world. Therefore, to characterize the dynamics of asset returns, we estimate a single VAR that treats Home and Foreign symmetrically.<sup>21</sup> The single framework described in this section summarizes concisely the information set available to both investors, although it is not in the format of the

> 20 We have analyzed more than these five reported specifications, but choose not to report them here. The results are qualitatively similar to those shown in this paper.

> 21 One of the VAR specifications considered here cannot be estimated by this unified framework; other control variables are needed. Thus, in this particular case, separate VARs are estimated for U.S. and Japanese investors.

24
points and taxes collected increased by a full percentage point.<sup>4</sup> But the tax adjustments are again significantly smaller for high-stakes declarations for which opportunities for graft are largest, suggesting opportunistic behavior by inspectors. Detailed comments also prolonged clearance times by encouraging inspectors to upgrade more declarations to the red channel and to do more scanning of their contents.

Within the set of declarations that received detailed comments, only the subset that contain specific quantitative metrics, including information on prices and/or referring to previous transactions, saw significant improvements in customs outcomes. The extent to which information improves customs outcomes thus seems to be correlated with its quality and precision. That finding would also explain why valuation advice by the third-party service provider (which is more precise and detailed) seems to have a much larger impact than the detailed comments provided in the RCT.

Explicit monitoring tags significantly increase the prevalence of scanning but none of the other customs outcomes for any declarations. This lack of effectiveness could be related to the timing of the RCT, which took place after a period of strikes and during the 2018/2019 presidential elections. Customs inspectors may have anticipated a change of senior customs leadership, which could have diluted their fear of sanctions for improper behavior. However, the ineffectiveness is also consistent with an enduring culture of impunity and absence of strong performance incentives. Only 6 percent of customs inspectors believe that non-ethical behavior was appropriately sanctioned and only 13 percent believe promotions were merit-based, according to a survey we conducted prior to the start of the RCT.

To interpret these results, some limitations of the study must be kept in mind. Most importantly, we are unable to measure whether information provision increased the prevalence of extortion by customs inspectors. We did conduct structured interviews with representatives from the private sector before and after the RCT. Although there were some (seemingly isolated) complaints about a select few inspectors using the RCT as an opportunity to demand additional bribes and delay clearance, the RCT does not appear to have induced a widespread change in the prevalence of extortive practices. Second and related, we use fraud records and tax adjustments made by the

> 4 While detailed comments appear to help inspectors detect fraud among declarations for which valuation advice was not issued, they do not change significantly most inspector actions and customs outcomes for declarations for which valuation advice is also issued. This may in part be due to imprecise estimates given a very limited number of declarations selected for valuation advice.

5
WPS3747 sellers of food products. Of course, the size of the domestic market and the resulting low exposure of agricultural sectors to foreign trade mentioned above are likely to dampen the impact of world price changes on the domestic market. In the urban areas, poor households could suffer from an increase in the price of food. The resulting overall poverty impact is thus difficult to predict and depends on the relative size of the efficiency and hence income gains generated by the removal of the import duties, and changes in the relative price of food.

# **2. Analytical Framework:  A Macro-Micro Model for Indonesia**

This section describes the specification of the Indonesia Macro-Micro Model used to analyze the social impact of various trade liberalization scenarios. A more detailed discussion of the specification and econometric estimates of the various equations of the household income generation model and simulation methodology may be found in Bourguignon, Robilliard, and Robinson (2003).

Our approach combines a micro-simulation model with a Computable General Equilibrium (CGE) model in a sequential fashion. The term micro-simulation spans a number of different approaches used in the social sciences. Their common denominator is to focus primarily on the economic behavior of agents and investigate the impact of public policy and shocks at the micro level. These models typically take representative samples of micro agents (households or firms) and measure the effect of government policy on these samples. Various micro-simulation techniques are described in more detail in the annex to the associated working paper (see also Cogneau _et al._ 2003).<sup>1</sup>

> 1 The interested reader is referred to the World Bank Policy Research Working Paper version of this chapter which has an extensive discussion of alternative approaches to micro-simulation.

4
This version: 15 Feb 2024 52 Bleynat, I., A.E. Challú, and P. Segal. 2021. Inequality, living standards, and growth: two centuries of economic development in Mexico. _The Economic History Review_ , 74: 584-610.

Block, Fred and Margaret R. Somers, 2014, _The Power of Market Fundamentalism_ , Harvard University Press Brockmann, Hilke, Jan Delhey, Christian Welzel, and Hao Yuan. 2009. "The China Puzzle: Falling Happiness in a Rising Economy," _Journal of Happiness Studies_ , 10(4), 387-405.

Campbell, A., P. E. Converse, and W. L. Rodgers. 1976. _The quality of American life: Perceptions, evaluations, and satisfactions_ . Russell Sage Foundation.

Cerra, Valerie, Ruy Lama, and Norman Loayza. 2021. "Links Between Growth, Inequality, and Poverty: A Survey," IMF Working Papers 2021/068, International Monetary Fund.

<mark>Clark, Andrew E., and Conchita D'Ambrosio. 2015. "Chapter 13 - Attitudes to Income Inequality: Experimental and Survey Evidence". Anthony B. Atkinson and François Bourguignon (eds.)</mark> _<mark>Handbook of Income Distribution</mark>_ <mark>, Volume 2, 1147-1208. prepublication copy: http://www.parisschoolofeconomics.com/clark</mark> <u><mark>andrew/ChapterNov232013.pdf</mark></u> <mark>Daryl Collins, , Jonathan Morduch, Stuart Rutherford and Olrlanda Ruthvan. 2009.</mark> _Portfolios of the poor: how the world's poor live on $2 a day_ <mark>. Princeton University Press.</mark> Crafts, N. 1997. Economic Growth in East Asia and Western Europe Since 1950: Implications for Living Standards. _National Institute Economic Review, 162_ , 75-84. doi:10.1177/002795019716200106 Department of Statistics, Malaysia (DOSM). 2020. “Household Income and Basic Amenities Survey Report, 2019.” Putrajaya, Malaysia.

Devarajan, S. and E. Ianchovichina. 2018. A Broken Social Contract, Not High Inequality, Led to the Arab Spring. _Review of Income and Wealth_ , 64: S5-S25.

Dollar, D., Kraay, A. Growth is Good for the Poor. _Journal of Economic Growth_ **7** , 195– 225 (2002).

Duesenberry, James S. 1949. _Income, Savings and the Theory of Consumer Behavior_ , Harvard University Press, Cambridge, MA.

52
**Table** 2: **Coverage of the Food Stamp Program by Eligibility Category**

||**(Percent)**||||
|---|---|---|---|---|
|_Category_|_1989_|_1990_|_1991_|_1992_|
|Households with children <5 years|20|16.6|26.2|27.3|
|Households with<br>pregnant and|||||
|lactating mothers|n.a.|0.5|7.2|2.5|
|Households with elderly|18.6|22.3|30.1|42.7|

_Source:_ Jamaica Survey of Living Conditions Report, various years -November 1989, 1990, 1991, 1992. Planning Institute of Jamaica.

**Table 3: Percentage of Households in Poorest and Richest Quintiles Receiving Food Stamp Transfers by Eligibility Category**

||_19_|_89_|_19_|_90_|_19_|_91_|
|---|---|---|---|---|---|---|
|_Category_|_Poorest_<br>_Quintile_|_Richest_<br>_Quintile_|_Poorest_<br>_Quintile_|_Richest_<br>_Quintile_|_Poorest_<br>_Quintile_|_Richest_<br>_Quintile_|
|Households with children|<br>34.6|5.3|||||
|<5 years|||||||
|Households with elderly|38.5|5.5|||||
|All Households|31.2|2.2|12.9|1.4|38.3|2.2|

_Source:_ Jamaica Survey of Living Conditions, November 1989, 1990, 1991.

In 1993, total costs of the program amounted to roughly 0.1 1 percent of GDP. During the period 1989-1992, the program reached between 12 and 20 percent of all Jamaican households (Table 1). During these same years, 30 to 40 percent of households in the poorest quintiles gained access to food stamps compared with 3 to 6 percent of households in the highest quintiles. These numbers illustrate the fact that the FSP has excellent targeting outcomes (compared to similar programs in other countries). With regard to access based on gender, Louat, Grosh and Van der Gaag (1993) found no 7