rafmacalaba/datause-encoder-data huggingface dataset:
8. Bloch, F. and Rao, V. (2002), ’Terror as a Bargaining Instrument: A Case Study of Dowry Violence in Rural India’, American Economic Review 93(4), pp. 1385-98.

9. Borooah, V. (2004) ‘Illuminating the Politics of Demography: A Study of Inter Community Fertility Differences in India’, European Journal of Political Economy, 20, pp. 551-578.

10. Borooah, V and S. Iyer (2005a), ‘Religion, Literacy, and the Female-to-Male Ratio in India’, Economic and Political Weekly, Special Issue on Religion and Fertility, January.

11. Borooah, V and S. Iyer (2005b), ‘ _Vidya, Veda_ and _Varna_ : The Influence of Religion and Caste on Education in Rural India’, The Journal of Development Studies, Vol. 81, Number 4, November, pp. 1369-1404.

12. Borooah, V and S. Iyer (2005c), ’The Decomposition of Inter-group Differences in a Logit Model: Extending the Oaxaca-Blinder Approach with an Application to School Enrolment in Rural India,’ Journal of Economic and Social Measurement, November, Vol. 30, No. 4, pp. 279-293.

13. Borooah, V. and S. Iyer (2004), ’Religion and Fertility in India: The Role of Son Preference and Daughter Aversion’, Cambridge Working Papers in Economics 436, Faculty of Economics, University of Cambridge.

14. Botticini, M and A. Siow (2003) ‘Why Dowries?’, American Economic Review, 93(4), pp. 1385-98 15. Caldwell J.C., Reddy P.H. and Caldwell P. (1983), ‘The Causes of Marriage Change in South India’, Population Studies 37 (3), pp. 343-361.

16. Chen, L. C. (1982), ‘Where have the Women Gone? Insights from Bangladesh on the Low Sex Ratio of India’s Population.’, Economic and Political Weekly, 17.

17. Coulson, N. and Hinchcliffe, D. (1978), ‘Women and Law Reform in Contemporary Islam’, in Women in the Muslim World, edited by L. Beck and N. Keddie, Cambridge: Harvard University Press, pp. 37-49.

18. Das Gupta, M. (2005), ‘Explaining Asia’s ‘Missing Women’: A Look at the Data’, Population and Development Review, 31(3).

16
billion of perpetual preferred stock to Berkshire Hathaway illustrates both the adverse effects that market participants can create when seeking liquidity at the same time and the important role that external investors with deep pockets can play in providing liquidity. We can expect households with higher wealth/income levels to buy illiquid assets that have dropped in price:

**H3c:** _Households with higher income and wealth levels are net buyers of illiquid stocks when aggregate market liquidity is low._

# **3. Individual Trade Data and Liquidity Measures**

The main dataset for this paper comes from a major U.S. discount brokerage house and includes the daily trading records of 78,000 households from January 1991 to December 1996. These households hold a total of 158,034 accounts of various types including cash, margin, IRA and Keogh. In this study, I focus on the common stock investments of the households, which constitute nearly two-thirds of the total value of their investments in the dataset. About 66,000 of the 78,000 households trade common stock, making close to two million trades over the sample period. The transaction record includes number of shares traded, price and any commissions paid. The dataset also includes each household‟s month-end positions including the value of security holdings at market close on the statement date. For a sub-sample of households, the dataset includes demographic information, such as income, age, gender, occupation and marital status. A more detailed explanation of the dataset can be found in Barber and Odean (2000, 2001). A comparison of this dataset with Survey of Consumer Finances, IRS and TAQ data has shown it to be representative of U.S. individual investors (Ivkovic, Sialm, and Weisbenner 2006, Ivkovic, Poterba, and Weisbenner 2005, and Barber, Odean, and Zhu 2006).

Liquidity is a multi-faceted concept, and is usually defined in terms of the costs and risks associated with transacting financial securities. These costs relate to exogenous costs of transacting including price impact, asymmetric information and inventory risk. Given the multi- faceted and unobservable nature of liquidity, I use a number of different 9
# **D. B Algorithm Choice**

Table D.1. Descriptive Statistics – Electoral and Municipal Baseline Controls

||PEP<br>(1)|No-PEP<br>(2)|Mean diff. (p-value)<br>(3)|
|---|---|---|---|
|_Panel A. Confict and Violence_||||
|Homicide rates (per 100,000 inh.)|14.190|2.388|0.003|
||(67.448)|(3.972)||
|Number of robberies|385.816<br>(3,653)|11.175<br>(14.634)|0.083|
|_Panel B. Public Finance_||||
|Revenue|81.554|13.620|0.051|
||(588.875)|(7.113)||
|Expenditure|32.850|2.899|0.146|
||(347.791)|(1.676)||
|Capital Expenditures|82.252|13.515|0.060|
||(616.664)|(7.173)||
|Central Government Transfers (SPG)*|27,070<br>(123,000)|6,878<br>(3,726)|0.005|
|SPG in education|12,728|425|0.011|
||(82,056)|(391)||
|SPG in health|8,127|2,320|0.000|
||(25,355)|(1,969)||
|SPG in sewage and water|1,641<br>(4,889)|727<br>(450)|0.002|
|SPG in child nutrition programs|188.248<br>(403.757)|73.683<br>(83.888)|0.000|
|SPG in children|162.116<br>(348.286)|72.740<br>(87.952)|0.000|
|_Panel C. Poverty and inequality_||||
|Rural index (% Rural population)|0.505<br>(0.248)|0.678<br>(0.172)|0.000|
|_Panel D. Economic Growth_||||
|Night Light Density|4.755<br>(8.126)|1.346<br>(2.130)|0.000|
|_Panel E. Previous Regularized Population_||||
|PEP1 (August 2017-October 2017)|83.540<br>(1,029)|0.640<br>(3.94)|0.174|
|PEP2 (February 2018-June 2018)|136.957|1.168|0.188|
||(1,743)|(4.866)||
|Observations|811|286|1,097|

_Notes:_ *SPG stands for _Sistema General de Participaciones_ and represents central government transfers to municipalities. Variables are expressed in millions of Colombian pesos, except for expenditures, which are expressed in thousands of Colombian pesos.

70
-

- Milesi-Ferretti, Gian Maria and Cédric Tille, 2011. "The Great Retrenchment: International Capital Flows during the Global Financial Crisis," Economic Policy, CEPR, CES, MSH, 26(66): 285-342.

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- Peek, Joe, and Eric S. Rosengren. 2000. "Implications of the Globalization of the Banking Sector: The Latin American Experience _." Federal Reserve Bank of Boston New England Economic Review_ (Sept-Oct):45–62.

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38
is at play: cities with strong current performance—surpassing the growth target by a wider margin— tend to withhold effort now to avoid facing a higher target in the future (Weitzman 1980). Indeed, using a regression discontinuity design (RDD), we find cities that truthfully achieved their targets are likely to report a growth smaller than the true growth, compared with those that just failed the target. In addition, they are more likely to report lower growth in their first year in the job when they could scapegoat their predecessors. The Chinese cadre management system thus has a built-in mechanism to contain GDP reporting, at least in some years.

Our paper contributes to two strands of literature. It is related to the literature on bureaucracy and development--see Besley et al. (2021) for a comprehensive survey.<sup>5</sup> Despite the large literature, the top area needing further research is aspects related to the measurement of bureaucratic performance (Besley et al. 2021).<sup>6</sup> Existing studies on senior bureaucrats often measure bureaucratic outputs as certain aggregate outcomes such as GDP growth (Li and Zhou 2005; Jia, Kudamatsu and Seim 2015), revenue generation (Xu 2018), or local development outcomes (Gulzar and Pasquale 2017). We add value by examining how the key performance measure of top local bureaucrats in China, GDP growth, is subject to bureaucratic manipulation, under prevailing career incentives. Such performance manipulation makes it harder to motivate bureaucrats, and could render the incentive design of tournament competition, often viewed as the key design behind China’s growth, less effective. We also show how the ratchet principle also limits the extent of performance manipulation in the Chinese bureaucratic system, and thus partially restores the effectiveness of the tournament competition system.

We also contribute to the literature on local government behaviors and local development in China, one of the most prolific areas of research for studying the contemporary Chinese economy. This literature has emphasized the role of incentives and the capacity of local government officials in accounting for local economic development in China. The prevailing view is that the promotional incentives shaped by tournament competition among regions strongly facilitated regional and therefore China’s growth (Maskin, Qian and Xu 2000; Li and Zhou 2005; Xu 2011). Others question this conclusion by pointing out the non-robustness of the link between promotional incentives and local growth (Landry 2003), and/or modifying the view by emphasizing complementary factors such as connections and factions (Shih et al. 2012; Jia, Kudamatsu and Seim 2015), or selection of talents (Yao and Zhang 2015). All these studies assume the reported growth rates are unbiased. We cast doubt

> 5 See also Dixit (1997); Evans and Rauch (1999, 2000); Khan, Khwaja and Oklen (2016, 2019); Finan, Olken and Pande (2017); Ashraf and Bandiera (2018); Rasul and Rogger (2018); Xu (2018); Bandiera et al. (2020); Bertrand et al. (2020); and Colonnelli, Prem and Teso (2020).

> 6 See also Asher and Novosad (2020), and Donaldson and Storeygard (2016).

5
can be a ratio of liability over assets, which is a continuous variable, over-indebtedness can be measured as a categorical variable showing whether a particular borrower’s liability exceeds a certain percentage of his or her asset values. Such a measure of indebtedness is based on stocks of cumulative debt and assets, and hence reflects medium and long-term measures of indebtedness.

Alternatively, indebtedness may be defined as the ratio of a household’s monthly repayments divided by its monthly net income, a short-term measure of indebtedness (Maurer and Pytkowska 2010). This indebtedness ratio itself, however, does not show when the borrower can be considered over-indebted, in which case a threshold is required to indicate at what point in the debt-income ratio a borrower is deemed over-indebted. Accordingly, a household may be over-indebted if the client spent more between 50 percent and 75 percent of its income on debt servicing.

In a study from Ghana, 26 percent of all respondents find it easy to repay their loans, while about one-third struggle occasionally, 26 percent struggle more frequently but not all the time, and 17 percent struggle permanently with every single installment (Schicks 2010). Some 28 percent of the microcredit clients are found severely severely indebted or over-indebted in a study from Bosnia and Herzegovina (Maurer and Pytkowska, 2010), and concludes that borrowing from multiple sources and over-indebtedness go hand in hand. In a study from Kosovo, 25 percent of the microcredit clients were found over-indebted in different degrees (Spannuth & Pytkowska, 2011). This study also finds that the level of indebtedness increases with the number of active loan contracts, and that women are less frequently insolvent than men (3 percent insolvency among women versus 7 percent among men). These studies suggest that over-indebtedness is a serious issue in some countries, and is prevalent among 25 to 30 percent of MFI borrowers. In other words, over-indebtedness seems higher than the conventional wisdom about microcredit would suggest.

6
currency. Specifically, they show that fiscal rule adoption is associated with a reduction in foreign currency borrowing of between 1 and 1.9 percentage points.<sup>9</sup> A related strand of the literature has studied the factors influencing the adoption of fiscal rules (IMF 2009; Hallerberg and Scartascini 2015; Elbadawi, Schmidt-Hebbel, and Soto 2015, Altunbaş and Thornton 2017; Badinger and Reuter 2017). These studies have found that the political landscape can be an important factor for adopting fiscal rules. Similarly, economic conditions may play a key role: higher levels of debt or an economic crisis might affect the likelihood that a fiscal rule is adopted. However, these studies do not examine how these factors influence the subsequent impact of the rules. In this paper, we analyze how the economic and political environments prevailing at the time of fiscal rule adoption shape their medium-term effectiveness. We consider some of the conditions that can be seen as determinants influencing the adoption of fiscal rules, while others are more incidental (i.e. reflecting the specific environment at the time of adoption).

# **3. Data and methodology**

To investigate the dynamic effects of fiscal rule adoption, we focus on the response of the primary balance. The primary balance excludes interest payments from the budget, which are largely outside the control of the incumbent government and do not reflect fiscal policies implemented in the current period. This measure, therefore, effectively summarizes how fiscal policy responds to debt sustainability concerns (Bohn 1998).

We study the response of the primary balance over a ten-year period following the introduction of fiscal rules. This timeframe allows us to observe both the immediate and medium-term effects of introducing fiscal rules. Differences could arise, among other things, due to changing conditions that initially supported the adoption of the rules, potentially weakening commitment over time.

Our sample includes 108 countries, also including countries that never adopted fiscal rules. With fiscal rules data available up to 2021, we study their adoption until 2012. This allows us to analyze the evolution of the primary balance over period of ten years. The

> 9 Chrysanthakopoulos and Tagkalakis (2024) present another recent study on the dynamic effects of fiscal rules, but their analysis uses a methodology that restricts the type of effects that can be measured (see Section 4). Surprisingly, their findings show that fiscal rules lead to lower primary balances in the medium term, and they associate this counterintuitive result to possible lower interest payments associated with the increased credibility of governments.

9
Figure 7 presents the Kernel density distribution of household per capita income for rural and urban respectively. For tractability, we follow Bourguignon’s analysis and assume log-normal distribution of income (Bourguignon, 2002). Simulated poverty headcount, measured by the percentage of population with a household per capita income below a certain level, is captured by the area under the density curve to the left of the poverty line. The results in Figure 7 and Table 3 suggest that given the assumption of log-normality of income distribution, over the period of 1989-2004, poverty reduction has primarily been a result of rising income. Despite the hypothetical effect of poverty increasing as a result of worsening distribution, the overwhelming growth effect on poverty reduction is irrefutable – poverty headcount reduced significantly throughout the country, in rural as well as in urban areas, and in coastal provinces and inland provinces.

**Figure 7 – Growth and distributional effects on poverty reduction** (All the province, 1989-2004)

<!-- Start of picture text --> Rural Urban<br>Poverty line: 768 yuans Poverty line: 768 yuans<br>(urban Liaoning 1989 price) (urban Liaoning 1989 price)<br>4 5 6 7 8 9 10 11 4 5 6 7 8 9 10 11<br>Real per capita household income (logarithmic scale) Real per capita household income (logarithmic scale)<br>1989 distribution Horizontal translation of the 1989 curve 1989 distribution Horizontal translation of the 1989 curve<br>2004 distribution 2004 distribution<br>.8 .8<br>.6 .6<br>.4 .4<br>Density Density<br>.2 .2<br>0 0<br><!-- End of picture text -->

**<u>Table 3 - Decomposition of changes in poverty into growth and distributional effects</u>**

||Simulate<br>1989<br>distribution<br>A|d povertyhead<br>2004<br>distribution<br>B|count (%)<br>Horizontal<br>translation of<br>1989 curve<br>C|D<br>Total effect<br>B-A|ecomposition(<br>Growth effect<br>C-A|%)<br> <br>Distributional<br>effect<br>B-C|
|---|---|---|---|---|---|---|
|All the provinces|||||||
|Rural|55.7|25.7|21.2|-29.9|-34.4|4.5|
|Urban|22.4|14.6|1.8|-7.8|-20.6|12.8|
|Coastal provinces|||||||
|Rural|50.9|16.3|13.3|-34.5|-37.5|3.0|
|Urban|14.5|4.9|0.2|-9.6|-14.3|4.7|
|Interior provinces|||||||
|Rural|58.7|31.2|27.1|-27.5|-31.6|4.1|
|Urban|26.9|20.5|4.7|-6.4|-22.2|15.8|

Note: 1.5 dollars-a-day (Purchase Power Parity, 1993 international price) translates into 768 _yuans_ 1988 Liaoning urban price.

11
# <u>Table A1.3: Notifications of SSG Measures by major users</u>

|<br>Member|<br>Number of<br>tariff items<br>reserved for|<br>Maximum numb<br>year, 1995 th<br>indicated in l|er in any one<br>rough year<br>ast column|Annual|
|---|---|---|---|---|
||SSG<br>application|Price-based<br>measures<br>applied|Volume-<br>based<br>measures<br>applied|Notifications<br>are available<br>for 1995<br>through<sup>b</sup>|
|Chinese Taipei<sup>e</sup>|n.a.|15|54|2007|
|Costa Rica|87|4|0<br>|2007|
|European Communities|539|17|27<sup>f</sup>|2006/2007|
|Hungary<sup>a</sup>|117|7|0|2004|
|Japan|121|16|61<sup>c</sup>|2007|
|Korea|111|8|13|2004|
|Norway|49|0|1|2006|
|Poland<sup>a</sup>|144|106<sup>d</sup>|0|2004|
|Slovakia<sup>a</sup>|114|0|4|2004|
|Switzerland-Liechtenstein|961|7|0|2006|
|United States|189|83|6|2006|

Source: WTO 2002 (covers 1995-2001) and country annual notifications available on the WTO Documents online website.

Notes: n.a. = not available a Acceded to the EU in May 2004.

b as of 09 January 2009.

c Second-largest number is 10.

d Second-largest number is 7.

e Acceded to the WTO 1 April 2002; first annual notification is for 2002.

f The number of tariff lines for which EC notifications indicate that the volumebased system was ‘made operational.’ EC notifications also state each year that no volume-based measure was ‘applied.’ There is no parallel notification for the EC price-based system.

53
further by incorporating a variable to account for the interaction between fluency and being Ashaninka. Figure 4 illustrates the results for Rasch scores, showing that the slope is steeper for Ashaninka students: in other words, for these students, the relationship between fluency and comprehension is stronger than for non-Ashaninka students (as also shown by correlation coefficients in Table 11). This may indicate that for the most disadvantaged children, working on fluency early on is even more important than with advantaged students, as it appears to have greater association with their ability to understand what they read.

**Figure 4. Estimated relationship between Fluency and Comprehension measures for Ashaninka and Non Ashaninka students***

<!-- Start of picture text --> 100<br>Non Ashaninka<br>90<br>Ashaninka<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Fluency (wpm)<br>Rasch score in ECE test<br>0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150<br><!-- End of picture text -->

* Based on M6: Y= α + β1(Fluency) + β2(Ashaninka) + β3(Fluency*Ashaninka)

Having said that, an increase in the fluency test predicts only a small increase in performance in the written test:<sup>39</sup> Improving fluency by one word per minute is associated with only 0.15 in the Rasch scores (Model 1 in Table 12). That is, between a student who could not read a word aloud, and a student who read 60 words per minute, the difference in the ECE test would be only 9 points in the Rasch scale (from 41.2 to 50.2). When other factors are held constant (gender, age, first language, preschool education, location and type of school), this difference would be 6 points (from 45.3 to 51.3, in Model 2). Figure 5 illustrates this improvement against the estimated difficulty level of the questions. Holding other variables constant (Model 2), an improvement in fluency from 0 to 60 words per minute would mean an increase in likelihood of answering two or three more questions correctly, but the student would remain at the literal level. A student reading at 90 words per minute would still remain at that level. Basically, if using linear regressions to understand this relationship, we would have to say that in order to be likely to answer all questions correctly a student should be able to read at a fluency level of 297 words per minute. Of course, this is not very sensible: nowhere in the world is a second grader expected to read, aloud, at that speed, or a college graduate, for that matter. This suggests that the relationship between fluency and comprehension is likely non-linear and discontinuous.

> 39 The possibility that this is due to the effect of multicolinearity is ruled out by the variance inflation factor (VIF), which is lower than 1.6 in all models.

38