rafmacalaba/datause-encoder-data huggingface dataset:
""........... "" " '

# LATVIA INTEREST RATES

(In percent per annum) <!-- Start of picture text --> 140 140<br>LENDING RATES 1/<br>120 120<br>100 Domestic currency 100<br>80 80<br>Foreign currencj,<br>60 s. /60<br>40 40<br>20 ... 20<br>MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN<br>1993 1994 1995<br>80 8<br>DEPOSIT RATES 1/<br>70 - 70<br>60 - 60<br>50 Domestic currency 50<br>40 > 40<br>30 30<br>Foreign currencp ' ,, \<br>20 ""''"-..... 20<br>10 10<br>MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN<br>1993 1994 1995<br>oc0 REAL INTEREST RATES 2/ .<br>80 80<br>60 60<br>40 , -0--w '., \LendL ,,.j^ ing rate 40<br>Deposit rate&,<br>20 20<br>0 6<br>_~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ I, 6llB<br>........... ~ ~ ~ ~ ~ ~ .*<br>-20 -20<br>MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEBVMAR APR MAY JUN<br>1993 1994 1995<br><!-- End of picture text --> Sources: The Bank of Latvia; and staff estimates. 1/ Three-month moving overage; credits and deposits of 3-6 months' maturity. 2/ Computed on the basis of the three-month moving average of the monthly inflation rate.

7
|**Table 5: Cor**|**relation of Vote**<br>**and Municip**<br>**_(Robust standard_**<br>(1)|**Buying with Villa**<br>**al Project Spendi**<br> **_errors in parenth_**<br>(2)|**ge Roads Projects,**<br>**ng**<br>**_eses)_**<br>|<br>|
|---|---|---|---|---|
||<br>Number of<br>roads projects<br>funded by<br>maor|<br>Number of<br>roads projects<br>funded by<br>maor|(3)<br>Share of projects<br>in 2008 total<br>spending|(4)<br>Share of<br>projects in 2008<br>total spending|
|**_Bivariate specification, without_**|y <br> **_and with district _**<br><sup>~~*~~</sup>|y <br> **_fixed effects:_**|||
|Vote Buying|0.58|0.54|0.10|0.09|
|(% respondents reporting that|(0.31)|(0.38)|(0.10)|(0.11)|
|<br>theyknow of vote buying)|||||
|**_Multivariate specification:_**|||||
|Vote Buying<br>(% respondents reporting it in<br>b)|0.65<br>(0.51)|0.90<sup>~~*~~</sup><br>(0.53)|0.065<br>(0.09)|0.09<br>(0.11)|
|gy|||||
|Mayor’s family reported as|-0.15|-0.23|0.03|0.03|
|major employer or landowner|(0.20)|(0.23)|(0.045)<br>|(0.05)<br>|
|Indicator variable = 1 if no clan|-0.30|-0.35|-0.08<sup>~~**~~</sup>|-0.06<sup>~~*~~</sup>|
|dominates municipalpolitics|(0.30)|(0.33)|(0.03)|(0.04)|
|Municipal dependency on|-0.04|0.03|0.35|0.37|
|national revenue share|(1.5)<br>|(1.5)<br>|(0.23)|(0.25)|
|Barangay/Municipality|-0.013<sup>~~**~~</sup>|-0.02<sup>~~**~~</sup>|0.0002|0.0002|
|<br>povertyestimate|(0.006)|(0.01)|(0.002)|(0.002)|
|Barangay/Municipal|-0.20|-0.21|-0.03|-0.03|
|population(log)|(0.18)<br>|(0.22)<br>|(0.03)|(0.03)|
|Barangay location (travel time<br>to_centro_)|0.01<sup>~~***~~</sup><br>(0.0025)|0.01<sup>~~***~~</sup><br>(0.002)|||
|Barangay roads need repair|0.003<br>(0.21)|0.12<br>(0.25)|||
|Barangay “social capital” (%|-0.04|-0.09|||
|reporting _bayanihan_)|(0.66)|(0.71)|||
|District FE|No|Yes|No|Yes|
|District 1||0.26<br>(0.36)||0.07<br>(0.06)|
|District 2||0.47<br>(0.33)||0.04<br>(0.06)|
|District 3||0.29<br>(0.31)||0.08<br>(0.07)|
|N R|58|58|30|30|
|, -sq|0.23|0.27|0.35|0.41|

36
- Ideally there should be one, clearly identified, central location where consumers of financial services and products can go when they have complaints or inquiries.

- The central complaints office should have a toll-free telephone line so that in case of a dispute, anyone from anywhere in the country can obtain information about financial services and consumers’ legal rights.

- Consumers should be able to submit their complaints by email, by postal mail, or by visiting the premises of the complaints office.

- Statistics on consumer complaints should be analyzed and published—and used to identify future improvements in the financial consumer protection framework.

- Policy-makers should consider alternatives to courts, such as a financial ombudsman office, that can take and enforce decisions regarding consumer claims for small amounts of money.

- A financial ombudsman office may be set up under a professional association or as an independent statutory ombudsman.

# **Financial Literacy & Education**

- The impact of different techniques of delivering financial education on financial literacy and on consumer behavior is evolving.  Programs to improve financial education should be rigorously tested and evaluated.

- Financial education for consumers should be focused on “teachable moments.”

- Middle and high-income countries should have national strategies on financial education and financial literacy. Low-income countries should develop financial education programs according to the country’s level of institutional capacity.

- The first step is to conduct a national survey of financial literacy, to be used as baseline. Followup surveys of financial literacy should be conducted every three to five years.

- Qualitative monitoring of consumer protection should be conducted, e.g. using “mystery shoppers”.

- Global surveys should be conducted of legal and regulatory frameworks for financial consumer protection, levels of financial literacy, and patterns of financial consumer behavior.

5
# **1. Introduction**

Arbitron, the radio ratings company, recently switched from surveys to 'Portable People Meters', an electronic device that directly records the listening habits of their large sample of listeners.<sup>1</sup> The move from self-reports to electronic recording resulted in a 10.7% drop in the estimate of the market share of classical music. Men proved to be listening to soft-rock much more than they had previously reported. Evidently when selfimage is involved, survey respondents are less than candid in their responses and candor differs across groups. This anecdote alone should sensitize researchers to the problems arising when surveying value-laden activities such as corruption. At the very least, if the proportion of candid respondents varies across groups, comparisons of responses to corruption questions across groups can be misleading. Cross-country comparisons will be similarly affected.

The purpose of the present paper is to examine the prevalence and consequences of such problems by using the responses from the World Bank sponsored Nigeria Enterprise Survey. This survey was fielded in two waves in 2008 and 2009, covering a total of 5422 firms. The survey posed questions on a wide range of aspects of business operations, such as financing, organization of production, economic performance, reactions to regulation, and obstacles to current operations. A significant number of questions focused on corruption, but these questions were by no means dominant in the survey. It seems unlikely that any respondent would have concluded that this was a corruption survey, _per se_ .

The obvious difficulty in assessing respondent candor is that there is nothing analogous to the 'Portable People Meters' for corrupt activities. What is needed is a technology that identifies those who are not candid and that relies solely on survey responses. This has been a long-sought element of the methodology of surveyors. Recently, Azfar and Murrell (2009) (AM) proposed such a methodology, which in a

> 1 "Never Listen to Céline? Radio Meter Begs to Differ" By Stephanie Clifford. _New York Times_ , December 16th, 2009.

2
5

# TABLE 2.2

# Value Added Tix Rates on Major Product Groups

May 1988

|Product Group|Rat|es|
|---|---|---|
|Textiles|14Z|-<br>232|
|Clothing and Footwear|14Z|- 202|
|Enamel Products||202|
|Glass and Glass Products|142|-<br>26Z|
|Medicines||14Z|
|Household Machinery|14%|-<br>43Z|
|Electrical Appliances|14%|-<br>20X|
|Electronic Appliances|142|-<br>16Z|
|Machinery|12%|-<br>14Z|
|Steel||8Z|
|Steel Products||14X|
|Paper|142|-<br>302|
|Stationery|122|-<br>302|
|HouseholdChemicals|142|-<br>452|
|Ceramics|122|-<br>202|
|Processed Food and Beverages|14X|-<br>302|
|Leather|142|-<br>202|
|Furniture||142|

Source: General Taxation Bureau

# Business Tax

The Business Tax replaced that part of the Consolidated Industrial and Commercial Tax that applied to wholesale and retail distribution, construction, transport and communications and services. It is applied to non-agricultural activities outside manufacturing: retail, wholesale, transport, construction, banking and insurance, telephones and telecommunications, publishing, utilities, entertainment and other services. It is a turnover tax on gross sales value in all sectors except wholesale where it is levied on the gross value of the mark-up. The rate structure is shown in Table 2.3.
The war in Bosnia took a heavy toll on the population. The most conservative estimates by the International Criminal Tribunal for the former Yugoslavia (ICTY) indicate that at least 102,000 people were killed during the conflict, and the UNHCR estimates that around 1.3 million people were displaced. After the peace agreement was signed, more than 1 million of the displaced people were “resettled” all over the country and by 2007, an estimated 460,000 returned to their place of origin (UNHCR, 2007). In 1996, 59 donor countries and organizations pledged $1.9 billion in support of the reconstruction effort.

# **3.2 Measuring Mental Health**

We construct our measures of mental health based on household survey data from the Living Measurement Standards Study (LSMS) survey in BiH.<sup>9</sup> These surveys were conducted in four consecutive years (2001, 2002, 2003, and 2004). Consumption and income aggregates are available only in the 2001 and 2004 waves, while mental health questions were asked in 2001, 2003 and 2004. The 2001 survey was nationally representative and contained over 5,400 households and more than 9000 individuals. We have information on the mental health status of nearly 7000 individuals from the 2001 survey; approximately 63 percent of them were reinterviewed in 2004. In our results, we will present comparisons using the full sample, as well as comparisons using only panel observations.

We construct consistent measures of mental health across the two waves using the questions which were common to both waves. These questions relate to having low energy, selfaccusation, and trouble with sleeping, feeling hopeless, feeling worried, feeling melancholic and feeling that “everything was an effort”. We find that in the 2001 survey, measures of mental health constructed using these 7 variables are highly correlated with the measures using the 14point CESD scale (the correlation is 0.96). In addition, as discussed in Section 2, the CESD scale has been validated, which constitutes an advantage over many other empirical studies.

There was also a separate question asking how often the respondent remembered the painful events experienced during the war, measured on a four-point scale similar to the other mental health questions. Answers to that question are moderately correlated with the overall

> 9 These household surveys were carried out by the World Bank, UNDP and DfID in co-operation with the Institute for Statistics of Republika Srpska (ISRS), the Statistics Institute of the FBiH and the Agency for Statistics of BiH.

12
Table 8: Political Influence, Competition and Output among Competitors ( _j_ )

|_Yh_ = Fewer than 20 competitors (Y=100)(Obs. 17,639)|(4)|(5)|
|---|---|---|
|Pol. Infuence|-0.072***|-0.651|
||(0.0175)|(0.395)|
|Constant|48.99***|49.31***|
||(0.865)|(1.563)|
|R-squared|0.926|0.926|
|Marginal Efect +1 SD in Index|-0.480|-4.346|
|p-val.|0.000|0.111|
|_Yh_ = Total Sales (log 2009 USD)(Obs. 16,990)|||
|Pol. Infuence|-0.007***|-0.057*|
||(0.002)|(0.031)|
|Constant|13.29***|13.24***|
||(0.057)|(0.045)|
|R-squared|0.947|0.948|
|Marginal Efect +1 SD in Index|-0.048|-0.378|
|p-val.|0.000|0.074|
|_Yh_ = Sales per Worker (log 2009 USD)(Obs. 16,841)|||
|Pol. Infuence|-0.002*|-0.010|
||(0.001)|(0.018)|
|Constant|10.40***|10.41***|
||(0.0288)|(0.0289)|
|R-squared|0.962|0.962|
|Marginal Efect +1 SD in Index|-0.015|-0.065|
|p-val.|0.080|0.591|
|_Yh_ = Labor Costs to Sales Ratio (log)(Obs. 15,021)|||
|Pol. Infuence|0.002***|-0.019|
||(0.000)|(0.019)|
|Constant|-2.062***|-2.111***|
||(0.025)|(0.0425)|
|R-squared|0.928|0.928|
|Marginal Efect +1 SD in Index|0.013|-0.125|
|p-val.|0.000|0.336|
|**_X_** co-variates|✓||
|**_X_** interacted w/Pol. Infuence||✓|
|Location FEs|by Sector|by Sector|
|Sector FEs|by Location|by Location|

* _p <_ 0 _._ 10 ; ** _p <_ 0 _._ 05 ; *** _p <_ 0 _._ 01

OLS estimates. Robust standard errors, with two-way clustering at the 2-digit ISIC and region level in parentheses, per Cameron et al. (2011). Co-variates (not shown) include the log of age, the years of the manager’s experience, dummy variables for exporters, foreign-owned firms, and those part of a larger firm.

These results match the specifications in Cols. 4 and 5 from Table 5. In those main specifications, we find that (relative to firm _i_ ’s industry-region, an increase in Political Influence is associated with a higher likelihood of a small number of competitors, greater sales, and higher sales relative to the number of workers and a lower relative cost share of labor. When looking at the averages across competitor firms in _h_ —that is firms in the same industry-region—by contrast, a 1 S.D. increase in firm _i_ ’s influence 33
<!-- Start of picture text --> Figure 6. House prices and residential investment<br>(in percent)<br>2000–2006<br>100<br>Change in House<br>ESP<br>Prices<br>80 FRA<br>(Percent) NZL<br>UK<br>60 BEL IRL DNK<br>AUS<br>CAN SWE<br>40 ITA USA NOR<br>FIN<br>20 NLD<br>CHE<br>0<br>DEU<br>-20<br>JPN Change in Residential Investment<br>(Percent)<br>-40<br>-20 0 20 40 60 80 100<br>2007–2008<br>4<br>Change in House<br>Prices NLD<br>BEL<br>(Percent) AUS<br>0 SWE CHE<br>FRA DEUITA<br>JPN<br>ESP FIN CAN<br>-4 UK NOR<br>USA DNK<br>-8 NZL<br>Change in Residential Investment<br>IRL<br>(Percent)<br>-12<br>-30 -25 -20 -15 -10 -5 0 5<br><!-- End of picture text --> Note: Each figure plots the percent changes in house prices and residential investment during the respective periods. The sample consists of 18 advanced economies.

57
# 3 Data

We now turn to the empirical evidence and analyze both price and quantity data. The price data are used to estimate risk premia on short and long-term bonds, and to characterize the behavior of the implied term premium. The quantity data are used to analyze the comovement between the maturity structure of bond issuance and the observed term premium.

We conduct the empirical analysis by collecting data on sovereign bonds from the early 1990s up to 2003 for eight emerging economies. These countries are Argentina, Brazil, Colombia, Mexico, Russia, Turkey, Uruguay, and Venezuela. To calculate the term premium, we also collect data on sovereign bonds for Germany and the U.S., which are assumed to be free of default risk. The choice of emerging markets is constrained by data limitations. To estimate time series of the term premium, we need enough foreign currency denominated bonds of different maturities at each point in time. Therefore, our sample corresponds to those emerging economies that borrowed heavily in foreign currency, generating a rich enough pool of bonds. Furthermore, we restrict the sample to sovereign bonds because they constitute the most liquid debt instrument in most emerging markets, and because private debtors in emerging markets do not issue enough bonds to compute the term premium.

We collect weekly (end-of-week) time series of bond prices, using all available bonds for each country.<sup>21</sup> We also collect other information on these bonds, including currency denomination, coupon structure, and maturity. In addition, we compile time series of bond issuance in foreign currency. For each bond, we collect the amount issued, currency denomination, and maturity date. With this information, we construct weekly time series of amount issued valued in U.S. dollars. We exclude from the sample the bonds with collateral and special guarantees, such as collateralized Brady bonds and those issued by Argentina during the large pre-default swap. We also exclude bonds issued during forced restructurings, like those issued by Argentina and Russia post default and Uruguay post crisis.<sup>22</sup> We collect data from three different sources: Bloomberg, Datastream, and J.P. Morgan.

Regarding the currency choice, we restrict the sample to bonds denominated in foreign currency because it is not possible to construct the term premium by mixing bonds with different risk

> 21 We eliminate the observations where bond prices do not change over time, as this typically re fl ects no trading.

> 22 See Duffie, Pedersen, and Singleton (2003) for more details on the Russian default.

16
Because of our partnership with the microfinance institution PALFSI, we anticipated that current clients might respond differently to treatment and have different characteristics from non-PALFSI clients. Envelopes were randomized by barangay and by microfinance client status in blocks of five. This procedure generated block randomization within 81 barangay-by-client-status stratification cells. Our regression estimates include indicator variables for each stratification cell as control variables.

# _Passport randomization_

Respondents in the passport survey were randomly assigned with equal probability to a control group or to one of two treatment groups prior to implementation. We stratified members of the passport sample by baseline treatment group, whether they had enrolled in Pilijobs.org, barangay, and age. Specifically, we divided members of this sample into groups based on baseline treatment assignment and Pilijobs.org enrollment status, divided each group into barangays, sorted by age within each barangay-sample cell, and blockrandomized by threes. These respondents were resurveyed and randomly assigned to a passport control group or to the passport information [T3] or passport assistance ([T3] + [T5]) interventions.

Our administrative records indicate that 9.6% of baseline respondents offered passport assistance successfully obtained a passport. Although the program provided a full subsidy of the cost of the passport and required documentation, as well as fully subsidized transport expenses, passport applicants still needed to devote substantial time and effort to obtain a passport. For example, each applicant traveled one to two hours to the regional office of the Department of Foreign Affairs in Legazpi City three separate times to apply for and receive their passport, and most applicants made additional trips to other 12
2

# **Introduction**

This paper poses and examines a significant puzzle in the political economy of infrastructure in India—the co-existence of relatively low shares of capital spending in public budgets alongside evidence of large demand from poor voters. Several separate household surveys in different states provide systematic empirical support for the conventional political wisdom that _bijli, sadak,_ and _pani_ (electricity, road, and water) rank at the top of voter demands, and dominate electoral rhetoric. Yet, across the major states of India, public spending on capital works has barely averaged 13 percent of total spending (excluding debt servicing and interest payments), in contrast to over 21 percent on recurrent education expenses.<sup>1</sup> Education, however, is cited far below infrastructure on citizen rankings of priorities for public action.<sup>2</sup> The argument offered here to explain this puzzle is that public infrastructure projects are particularly suited to political rent extraction, the benefits from which are traded-off against the electoral gains from delivering infrastructure as a broader public good.<sup>3</sup> At the same time, targeted provision of employment and welfare transfers to the poor can be more effective in ensuring their favorable vote, while the vote returns to delivering infrastructure as a public good can be more uncertain (relative to the provision of targeted benefits). Infrastructure provision,

> 1 Author’s calculations using detailed data on state finances published in annual issues of the Reserve Bank of India Bulletin, for the period 1980-2005.

> 2 Data collected by Besley et al (2004) through a survey of more than 5000 rural households in 3 states in the south—Andhra Pradesh, Karnataka, and Tamil Nadu—shows the overwhelming majority of respondents (more than 89 percent) citing either water works or general village infrastructure among the top problems with public services in their village; in contrast, education is mentioned by less than 6 percent of the households. Rural household surveys in the north Indian states of Uttar Pradesh by Banerjee et al (2007), and in Rajasthan and West Bengal by Chattopadhyay and Duflo (2004) similarly reveal roads and water as the top ranked priorities for public action, with education trailing behind.

> 3 This chapter does not distinguish between political rent-seeking as private kick-backs for political agents from projects (corruption), versus rent-seeking through the servicing of elite economic interests (elite capture), from which political agents may either benefit directly if they overlap as the economic elite, or through kick-backs or campaign finance. Both types of rent-seeking would lead to policy choices that deviate from what a benevolent and utilitarian social planner would adopt.
of total shares traded to average real market capitalization) and the number of listed companies in the stock exchange.

- (f) _Bond market development_ . We use indicators of the level of activity of domestic bond markets such as private bond market capitalization (private domestic debt securities issued by financial institutions and corporations) and public bond market capitalization (public domestic debt securities issued by the government) deflated by GDP in logs.

_Financial openness_ is measured as the ratio of foreign assets to GDP, foreign liabilities to GDP, and foreign assets and liabilities to GDP. To construct these ratios we use the data on foreign assets and liabilities from Lane and Milesi-Ferretti (2001, 2007a) and updated (at best) until 2007 with data from international investment positions published by the central banks. Note that holdings of foreign assets (and/or liabilities) imply the accumulation of holdings of assets (and/or liabilities) in foreign direct investment, portfolio equity, debt (portfolio debt and other investment), and financial derivatives.

To assess whether the hoarding of risky vs. riskless assets or the accumulation of equity vs. debt liabilities affects the development of domestic financial institutions, we decompose our measure of financial openness into equity- and loan-related foreign assets and liabilities. Equityrelated assets and liabilities comprise information on direct investment and portfolio equity assets and liabilities. Loan-related assets (or riskless assets) include debt assets and reserve assets while loan-related liabilities include debt liabilities and financial derivatives liabilities (for the few countries that report them).

Among the _control variables_ in our regression analysis we include: real output measured by the PPP-adjusted real GDP from Heston, Summers and Aten (2006), inflation (lagged) as measured by the average annual change in consumer price index (from WDI), and trade openness approximated by the real value of exports and imports as a percentage of GDP. We also include two categories of _exchange rate regimes_ from Ilzetzki, Reinhart and Rogoff (2008): _dual exchange rates_ and _freely falling exchange rates_ . The former variable is a binary variable that takes the value of 1 whenever there is a dual market and parallel market data is missing. The latter takes the value of one for countries that have the annual inflation of more than 40% of inflation or that experience currency crisis. The _level of institutional quality_ is measured by the index of political risk by International Country Risk Guide (ICRG) and includes information on corruption, rule of law, democratic accountability, bureaucratic quality, investment profile, 8