rafmacalaba/datause-encoder-data huggingface dataset:
19 prices would be determined through a market mechanism. The so-called "tender" system was proposed by the Ministry of Labor to eliminate the guess-work in price setting and enable labor to respond to market signals. Intended to work like the system in place for Certificates of Entitlement for cars, the tender system would allow employers to bid for extra work permits above the dependency ceiling; permits would be issued for a duration of 2 years, and each sector would have its own system and market for exchange. Despite the economic efficiency arguments supporting the new system, however, the proposal was withdrawn due to opposition from unions (seeking to protect the jobs of their members) and employers (who feared uncertainty in labor costs and labor supply).<sup>10</sup> Overall, the Singapore experience provides an example where the interaction between immigration and macroeconomic policies was mutually reinforcing, in some ways improving the effectiveness of both. Policy makers have managed foreign labor resources in conjunction with the performance of the macro-economy, easing permit requirements to attract particular skills, or alternatively tightening requirements to shed labor during economic downturns, thereby using foreign labor as a buffer against economy-wide shocks. On the other hand, the failure of attempted policy reform in terms of the proposed tradable permit system illustrates the potential role of vested interests and political economy vis-a-vis immigration policy and labor demand. It is easy to conceive a situation in which poorly integrated policies generate contradictory incentives. Singapore's track-record highlights the importance of careful and comprehensive policy that is not undermined by existing distortions.

# **IV. Trends in the composition of labor**

Based on the robust economic performance of Malaysia and Singapore during the last decade and in view of their reliance on expatriate labor, general conclusions can be drawn regarding their successful management of the large foreign labor force through immigration policy and complementary measures. Is there more substantial evidence of policy effectiveness in managing foreign workers? Micro-level data exists for both Singapore and Malaysia, generated through periodic labor force surveys and household income and consumption surveys; although only summary data is available for Singapore, recent

> **10** Manufacture **r** s eportedly worried that multi-national corporations would have a comparative advantage in buying up permits _(Straits Times,_ October 7, 1991). Although the existing two-tier system is less efficient and less responsive to the market, they argued, at least it provides flexibility at a known price. In the existing tight labor market, it was feared that permit prices would be very high and that concomitant speculative behavior would increase uncertainty.
# **4 Research Design**

## **4.1 Overview**

Figure 1 provides a graphical summary of the research design. Our intervention is designed as an information provision experiment and administered through a phone survey with our partner bank’s credit card customers. In addition to survey data, we observe pre-treatment and post-treatment administrative data covering the universe of credit card transactions for all participants of our study.

The intervention proceeds in the following four steps. First, all respondents are asked a set of standard questions on demographics and their general economic situation. Second, a survey module elicits macroeconomic expectations and provides randomly selected subsets of respondents with information about inflation, the exchange rate, or both. Third, we measure posterior beliefs to assess whether our information treatments affect respondents’ expectations. Finally, we combine survey responses with administrative data on credit card spending to test whether the information provided affects subsequent consumption in the manner predicted by economic theory. We provide additional details on each of these steps in the following sections.

## **4.2 Sample Population**

To construct the sample frame for our experiment, we first requested a list of credit card customers from our partner bank. We specified that this list should be restricted to customers who opened their accounts within the previous three years. We received a random sample of 33,000 credit card customers and invited these customers to participate in a phone survey, which included our information experiment.

The survey was conducted by a team of 11 call center operators who were trained to administer a short phone survey and supervised in person by a member of the research team. At the beginning of each workday, the operators were provided with a randomly selected list of credit card customers to call. The operators introduced themselves as surveyors working on behalf of researchers from UCLA and asked participants if they were willing to participate in a short survey about their economic expectations. If operators were unable to reach a respondent on the first attempt, they were instructed to make at least one further attempt at a later time.

## **4.3 Information Experiment**

We integrated our experiment into this credit card customer survey administered by our partner bank. The survey instrument, which is available in C, can be divided into five parts: (i) collecting baseline information, (ii) eliciting prior beliefs, (iii) providing information to a random subset 10
# **1. Introduction**

Corruption hinders firm productivity by diverting resources away from their best uses. It does so, among other channels, by increasing the premium on rent seeking, creating secrecy and uncertainty and undermining public resources. Corruption also promotes excessive regulation, further empowering bureaucrats to extort rents and amplifying corruption’s negative effects on productivity (e.g. Shleifer and Vishny 1993; Banerjee 1997; Aidt 2016). Adverse effects of corruption on talent, investment, innovation, entrepreneurship, growth and public resources are well documented in the literature (e.g. De Soto 1989; Murphy et al. 1991, 1993; Mauro 1995; 1998; Tanzi and Davoodi 1997; Wei 2000; Djankov et al. 2002; Gamberoni et al. 2016; d'Agostino et al. 2016; Cieslik and Goczek 2018).

Empirical studies such as Meon and Sekkat (2005) and De Rosa et al. (2010) show that corruption is more damaging for economic performance at higher levels of regulation or lower levels of governance quality. Some studies also find that corruption eases the burden of excessive regulation and thereby improves economic performance (e.g. Leff 1964; Lui 1985; Dreher and Gassebner 2013). However, as pointed out in several studies, such as Campos et al. (2010), there is no widespread evidence for the latter. One reason is that corruption may speed the bureaucratic process in the short run, but in the long run, it will lead to more regulation and cause more damage in the economy.

Building on the above literature, in this paper, we use firm-level survey data on 39,732 firms in 111 countries collected by the World Bank’s Enterprise Surveys between 2009 and 2017 to test the hypothesis that corruption impedes firm productivity more at higher levels of regulation. Corruption is measured with three indicators: bribe rate (measured as the percentage of bribes in firms’ sales), bribery incidence (percentage of firms from which bribe is requested by public 2
of only chicken would cost 273,420 rupiah per month. Obviously diet of only rice and cassava flour is unrealistic and unpalatable and is not consumed, even by the very poor. People are quite willing to sacrifice calories for variety and taste in a diet. In addition, calories are just a proxy for an overall nutritional adequacy, which requires proteins and micronutrients as well as calories, and hence a varied diet is important for other reasons, while the total amount of calories is fixed "absolutely" the _basket_ and _quality_ of those foods used to reach that level is ultimately a _social convention._ That is, the basket must be fixed, but the fixing of the basket, while based on reasonable criteria, is ultimately a social choice.

The method we use to choose the basket is common: use a basket of foods actually consumed by a "reference population" to fix the _mix_ of foods and their prices, then the _total_ is fixed by scaling the mix of foods up to achieve the level of 2,100 calories. More formally, let **_i_**<sup>**_1_**</sup> **_k_** denote the average quantities consumed of commodity k by the reference population, which is chosen on the basis of its level or real expenditures. The food poverty line basket is defined as the set _qk_ = _Oq*k_

**_K_** _k= 1,_ ..., K, where 9 = 2,100 _/qkck_ and _Ck_ is the unit calorie value of **_k=1_**

commodity k.

Estimated food poverty lines can be rather sensitive to the choice of the commodity basket (Chesher, 1998). In order to make our estimates as directly comparable as possible to those constructed by BPS, we use 52 commodity items following the practice adopted by BPS (BPS and UJNDP, 1999). The list of these 52 commodities is given in table Al in the appendix. Once the food basket has been 4
# Table 2. Number of workers and labor intensity in the benchmark (in physical units and %)

||Young<br>workers|Female<br>(Unskilled)|Female<br>(Laborers)<br>|Female<br>(Technicians)<br>|Female<br>(Professionals)|Male<br>(Unskilled)<br>|Male<br>(Laborers)<br>**Number o**|**f workers**<br>Male<br>(Technicians)<br>|<br>Male<br>(Professionals|) <sup>Subsistence</sup>|Capital|Land|All females|All males|Adult<br>(females<br>+males)|<br>**Total**<br>**Number of**<br>**workers**|**Ratio:**<br>**All**<br>**All males**<br>|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**Business Services**|1,248|1,582|6,092|564|599|9,634|82,464|7,027|5,013|-|-|-|8,837|104,137|112,975|**114,223**|**0.08**|
|**Dixit-Stiglitz Goods**|12,497|3,108|34,609|1,129|566|12,527|68,826|4,235|610|22,965|-|-|39,412|86,198|125,610|**138,107**|**0.46**|
|**Agriculture**|2,858,933|30,730|3,825,359|2,537|0|117,406|3,199,983|4,202|1,571|3,939,135|-|-|3,858,627|3,323,162|7,181,788|**10,040,722**|**1.16**|
|**Other CRTS**|591,038|303,606|386,820|109,178|11,464|165,564|693,025|220,259|30,389|148,478|-|-|811,067|1,109,237|1,920,305|**2,511,342**|**0.73**|
|**ALL SECTORS**|3,463,716|339,026|4,252,880|113,408|12,629|305,131|4,044,297|235,723|37,583|4,110,578|-|-|4,717,943|4,622,734|9,340,678|**12,804,394**|**1.02**|
|||||||**L**|**actor inte**|**nsity (in**|**%)**|||||||||
|**Business Services**|1.09|1.39|5.33|0.49|0.52|8.43|72.20|6.15|4.39|-|-|-|7.74|91.17|98.91|100|-|
|**Dixit-Stiglitz Goods**|9.05|2.25|25.06|0.82|0.41|9.07|49.84|3.07|0.44|_-_|_-_|_-_|28.54|62.41|90.95|100|-|
|**Agriculture**|28.47|0.31|38.10|0.03|0.00|1.17|31.87|0.04|0.02|-|-|-|38.43|33.10|71.53|100|-|
|**Other CRTS**|23.53|12.09|15.40|4.35|0.46|6.59|27.60|8.77|1.21|_-_|_-_|_-_|32.30|44.17|76.47|100|-|
|**ALL SECTORS**|27.05|2.65|33.21|0.89|0.10|2.38|31.59|1.84|0.29|-|-|-|36.85|36.10|72.95|**100**|**-**|

Note: For the conversions of occupations to labor categories see note in Table 1. “Labor intensity” is the percentage weight of the number of workers of each category in the total number of workers. The percentages in the columns “Young workers” and “Adult (females+males)” add up to 100 as reflected in the column “Total number of workers”, since they represent all the labor available for production in the model, excluding the labor allocated to subsistence. In turn, the values in the column “Adult (females+males)” are the sum of the values in columns “All females” and “All males”.

Source: Author's calculations based on NBS (2002a).

27
insucient management training and lack of market competition.<sup>25</sup>

# 4.4 Rent-seeking

Another potentially important source of misallocation in Brazil is rent-seeking. A few recent papers have explored rich data sets to examine the eects of patronage and corruption on public employment selection and rm performance in Brazil. Colonnelli et al. (2020) use a detailed matched employer-employee data on the universe of public employees in Brazil over 19972014 and a regression discontinuity design in close electoral races to examine the role of political connections for public employment selection in Brazil. In particular, they empirically investigate whether discretion in public employment decisions is used as a patronage tool, and the consequences on the selection process in the context of the Brazilian public sector. Patronage represents an obvious friction in the selection of a high-quality public workforce, since political support can act as a substitute for individual competence in the process of government hiring. They establish three main ndings. First, political connections are a key and quantitatively large determinant of employment in public organizations in Brazil, for both bureaucrats and frontline providers. Second, patronage is an important mechanism behind this result. Third, political considerations lead to the selection of less competent individuals. In addition to patronage, there is recent evidence on the eect of corruption on rm performance in Brazil. Colonnelli et al. (2020) estimate the economic eects of a randomized anticorruption crackdown on local economic activity. On average, they nd a 0.9 percent increase in the number of rms and business establishments operating in treated municipalities in the three years after the audit. They also nd that audits increase real economic activity, with an increase in sales by local rms by about 6 percent. There is also evidence of large spillover eects, as a nearby audit has an impact on non-audited municipalities that is similar to their main eects. They also show that their magnitudes can be rationalized by an average corruption tax on rms in the range of 5-23 percent. Finally, they provide evidence that is informative of the role of corruption as a source of misallocation across rms. Consistent with the presence of a corruption tax, they nd that incumbent rms in government-dependent sectors grow the most after an audit. On the other hand, politically connected rms shrink considerably, suggesting that a potential channel through which corruption aects local economic activity is by allowing connected but inecient rms to operate and stie competition. They conclude the paper by highlighting the central role

> 25Ranasinghe (2020) nds substantial dierences in the extent of misallocation across male and female establishments spanning over 75 low and middle-income countries. In South American and South Asian countries female establishments face higher distortions on production, whereas in Eastern European countries male establishments face higher distortions.

22
- McCrary, J. (2008). Manipulation of the running variable in the regression discontinuity design: A density test. _Journal of Econometrics_ 142(2): 698-714.

- <mark>Nguyen, C., and Tran, A. (2017). The effect of having children on women’s marital status: Evidence From Vietnam.</mark> _<mark>Journal of Development Studies</mark>_ <mark>, vol. 53(12), pages 2102-2117.</mark>

- Nollenberger, N., & Rodríguez-Planas, N. (2011). Child care, maternal employment and persistence: a natural experiment from Spain, IZA Discussion Paper No. 5888, IZA Institute of Labor Economics.

- Quisumbing, A.R., Hallman, K. and Ruel, M.T., (2007). Maquiladoras and market mamas: Women's work and child care in Guatemala City and Accra. _Journal of Development Studies_ , 43(3): 420-455.

- Rivers, D., and Q. H. Vuong. (1988). Limited information estimators and exogeneity tests for simultaneous probit models. _Journal of Econometrics_ , 39: 347–366.

- Schlosser, A. (2005). Public preschool and the labor supply of Arab women: Evidence from a natural experiment. _Working paper,_ Hebrew University of Jerusalem.

- Staiger, D., and Stock, J. (1997). Instrumental variables regression with weak instruments. _Econometrica, 65_ (3), 557–86.

- Van Der Klaauw, W., (2002). Estimating the effect of financial aid offers on college enrollment: a regression-discontinuity approach. _International Economic Review_ 43, 1249–1287.

- <mark>Winther, T., Matinga, M.N., Ulsrud, K. and Standal, K., (2017). Women’s empowerment through electricity access: scoping study and proposal for a framework of analysis.</mark> _<mark>Journal of Development Effectiveness</mark>_ <mark>,</mark> _<mark>9</mark>_ <mark>(3), pp.389-417.</mark>

- Wooldridge, J. M. (2010). _Econometric Analysis of Cross Section and Panel Data,_ Cambridge, Mass.: MIT Press.

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26
<!-- Start of picture text --> 1960 1970 1980 1990 2000 2010<br>Year<br>IDA USA<br>3<br>2<br>1<br>Donor Rank z-score<br>0<br><!-- End of picture text --> Figure 1: The vertical axis shows the z-score of the average rank of IDA and the USA across IDA-recipients in a given year in terms of its share in aid disbursements. Aid disbursements exclude debt relief, humanitarian -, and food aid. A larger z-score indicates a better ranked (larger) donor. Data Source: DAC, Table 2a (OECD).

We calculate the sectoral overlap for ML _i_ at time _t_ by where _aist_ is aid disbursed by ML _i_ in sector _s_ in year _t_ , _ait_ is all aid disbursed by ML _i_ in year _t_ . _bst_ is the average share of aid disbursements in sector _s_ in year _t_ by all bilateral donors as shown in Table 1. We calculate OL _it_ for bilateral donors as well, but we then calculate the share of bilateral donors – _bst_ – for all bilateral donors other than this donor. We also produce similar measures for recipient overlap, i.e., with _s_ indexing recipient countries in (1), and recipientsector overlap, i.e. with _s_ indexing sector-recipient pairs in (1). Table 3 shows the results.

This table reveals that there are two types of multilateral agencies, in terms of their overlap. On the one hand, most agencies have either low sectoral or low geographic overlap (or both) with the average bilateral donor. For vertical funds such as the Global Fund (GLF), GAVI, and Global Environment Facility (GEF) the overlap is between 13% and 6%, meaning that only 13 to 6 percent of their budget overlaps with the budget of the typical bilateral donor. These agencies strongly specialize in only one sector, whereas the typical bilateral donor disburses 8
al. (2010a,b) may translate into unorganized sector, which accounts for the vast majority of Indian employment.

Our work is more broadly related to recent studies of Indian manufacturing productivity development (e.g., Kathuria et al. 2010, Trivedi et al. 2011, Bollard, Klenow, and Sharma 2013). In particular, many scholars today argue that India still contains extensive misallocation of activity across plants and regions (e.g., Hsieh and Klenow 2009, Desmet et al. 2011). The patterns identified in this paper highlight an important difference across firms in their input access or usage, which then correlates with lower productivity. These patterns help open up lines of potential inquiry about the reasons for these differences and their persistence as sources of misallocation. In this paper we observe a limited cross-sectional role for local industrial diversity, but more complex spatial dynamics may still exist.<sup>2</sup> The remainder of this paper is as follows: Section 2 describes the data used for this paper and Section 3 describes the broad patterns of input usage across sectors of Indian manufacturing. Section 4 analyzes the traits of districts and industries that are associated with higher input usage. Section 5 estimates the link between higher counts of distinct inputs and manufacturing productivity at the establishment level. The final section concludes and provides some thoughts about future work.

# **2. Indian Manufacturing Data and Usage Information**

This study employs cross-sectional surveys of manufacturing establishments carried out by the government of India in 2000-2001 (hereafter, we will only refer to the initial year of 2000 for simplicity). The organized and unorganized sectors of Indian manufacturing are surveyed separately. The organized sector comprises establishments with more than 10 workers if the establishment uses electricity. If the establishment does not use electricity, the threshold is 20 workers or more. These establishments are required to register under the India Factories Act of 1948. The unorganized sector is, by default, comprised of establishments which fall outside the scope of the Factories Act. The organized sector accounts for over 80% of India’s manufacturing

> 2 The literature surrounding the specialization and diversity of cities includes Jacobs (1969), Porter (1990), Glaeser et al. (1992), Henderson (1997), Feldman and Audretsch (1999), Duranton and Puga (2000, 2001), and Lall et al. (2003). Henderson (2010) provides a broader review of the role of cities in developing countries.

4
13 the relationship between crime and inequality within and between racial groups in South Africa.

# IV. Empirical Strategy

Empirically, we first establish the simple correlation between inequality and various types of crime in South Africa across police station jurisdictions. Next, we consider whether the observed relationships are more consistent with the economic or sociological theories of crime, by controlling for costs and benefits of crime and by comparing the results for violent and property crimes. We also examine the effect on crime of the relative position of a community among neighboring communities in terms of its wealth. Finally, we analyze whether inequalities between racial groups are more relevant in explaining crime levels than inequalities within racial groups.

The dependent variable for the analysis is the number of crimes reported by police station jurisdiction. We regress crime counts by jurisdiction on inequality and a varying set of regressors, always including jurisdiction population as a control, along with dummy variables for each of the nine provinces in South Africa. Because crime counts are discrete and there are zeros and small values in a non-negligible number of police station jurisdictions, we utilize a negative binomial regression model.<sup>7</sup>

# _Data_

7 See Greene (1997), pages. 931 - 940 for a fuller discussion of models for count data. Goodness of fit tests (as implemented in STATA) has indicated overdispersion, so we have opted to utilize a negative binomial model, of which the Poisson model is a special case.