rafmacalaba/datause-encoder-data huggingface dataset:
Besides studying international capital control liberalization, we investigate the empirical association between three regulatory indicators and measures of stock market integration, size, liquidity and volatility. The three regulatory measures are (a) the availability and quality of published information on listed fins, (b) the level of accounting standards, and (c) the intensity of investor protection laws. We obtain these measures from the International Financial Corporation's assessment of the institutional features of emerging stock markets from 1986-1993. We do not believe that previous authors have studied the links between these regulatory features and stock market functioning. The data do not suggest a robust empirical relationship between stock market integration, size, liquidity, and volatility and the official imposition of internationally accepted accounting standards or investor protection laws. Thus, the data do not support the contention that imposing internationally accepted accounting and investor protection rules will promote stock market development. However, countries with firms that widely disseminate comprehensive infornation have larger, more liquid, and more internationally integrated stock markets.

We organize the paper as follows. Section I describes the stock market indicators and policy events in our study. Section II then evaluates whether stock markets developed following the policy changes and Section III presents results on the relationship between regulatory regimes and stock market development. Section IV concludes.

3
inorganic fertilizer use is profitable and how that varies across space, the profitability of subsidized fertilizer vs. an equivalent cash transfer to beneficiaries, and the profitability of government recommend fertilizer application rates vs the actual application rates of smallholders in our sample. The study adds to the fertilizer profitability literature by controlling for plot-level unobserved heterogeneity, in addition to considering various maize prices that farmers face across time and space, and by relating the estimates to the geographical targeting of large-scale fertilizer subsidy programs.

The main results of our study suggest that when we assume farmers face positive transaction costs when using fertilizer, the input is on average not profitable at commercial price of fertilizer when maize is valued at either the farm gate price or lean season market price. The study also finds that, in order to make fertilizer more profitable at prevailing market conditions, the current average nitrogen use efficiency of 11.89kg would have to increase by at least 137.17% and by 50.46% if maize output is valued at farm gate price and lean season market price, respectively. Though these NUE estimates are lower than those used in other recent studies, such as Dorward et al. (2008), Arndt et al. (2015) and Harou et al. (2017) our use of recently collected nationally representative panel data on smallholders using plot-level FE could provide internally and externally valid estimates that are useful for policy analysis.

Our results are consistent with Arndt et al. in that our NUE of 11.89 suggests that FISP does not break-even. This is why we find that at all rates of subsidy, unless farmers are able to store their produce and sell in the lean season, the average farmer is MK 66.16 (US$ 0.18) per kg of subsidized nitrogen better off with the cash equivalent of the subsidy than participating in the subsidy program if maize is valued at the farm gate. Finally, the study finds that, compared to the current rate of nitrogen application, the government recommended rate is 116% to 119% more profitable depending on the price at which maize is valued.

27
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Table 4: In-sample Estimation Results for the Money <u>Gap Models</u><sup>a</sup>

||mgapm|bmodel|mgapm|1 model|Mgapm2 model|
|---|---|---|---|---|---|
|Constant|0.014|(3.21)|0.013|(3.21)|0.018 (4.09)|
|∆pt-1|0.387|(7.00)|0.381|(7.17)|0.434 (8.51)|
|∆pt-4|||||-0.071 (1.39)|
|∆pt-5|0.140|(2.41)|0.143|(2.61)|0.141 (2.75)|
|∆pt-6|0.122|(2.03)|0.095|(1.74)||
|∆pt-8|-0.012|(0.21)|0.003|(0.61)|0.057 (1.18)<br>|
|mgapt|||||-0.136 (5.30)|
|mgapt-1|0.388|(2.00)|0.075|(4.81)|0.194 (7.53)|
|mgapt-4|0.062|(3.00)|0.035|(2.44)||
|mgapt-8|-0.045|(2.26)|-0.029|(2.20)||
|1994.4 dummy|0.162|(10.9)|0.163|(11.2)|0.168 (11.8)|
|2001.4 dummy|0.045|(3.03)|0.045|(3.28)|0.029 (2.09)|
|**_Other Statistics_**<br>||||||
|R<sup>2</sup><br>|0.|626|0.|671|0.687|
|Adjusted R<sup>2</sup>|0.|602|0.|647|0.669|
|S.E.E|0.|014|0.|014|0.013|
|Jarque-Bera|5.|679|2.|251|0.096|
|LM AR (12)|20.|079|23.|806|28.833|
|LM ARCH (12)|12.|621|11.|104|8.551|
|White-Heteroskedasticity|10.|890|15.|602|8.935|
|RESET|2.|349|0.|260|1.608|

a: Figures in parentheses are the absolute value of the t-ratios.

# **4.3 Phillips Curve**

In estimating equation (8), I use the nominal USD exchange rate and a measure of the output gap estimated by Paşaoğullar ı and Yurttutan (2002). Their study employs Kalman Filter methodology by following the same approach taken by Boone et al. (2002).<sup>22</sup> In the estimation, I rely on the AIC to select the lag length of each variable. In this respect, the investigation considers all possible combinations up to 8 lags and then

> 22 Output gap measure in original series is quarterly, which are converted into monthly  frequency using RATS 5.0 distrib procedure. This procedure maintains the sum of three months equal  to the value at the quarter. We have adjusted so that the average of three months, rather than the  sum, is equal to the quarter value. For example, the average of output gap measure for the first three months of 2000 will be equal to the output gap at the first quarter of 2000.

25
where job seekers live, I can therefore control for factors unobserved by the employer. The rationale for this robustness test is as follows: assume that the residential location ( _zi_ ) is correlated with the number of profile clicks after controlling for other covariates, i.e. it was previously subsumed in the error term ( _ei_ = _vi_ + _zi_ ). Instead of specification (1), I now control for the residential location ( _zi_ ) non-parametrically by including dummies for each 0.5x0.5 grid cell: This unobservable variable explains an additional 20% of variation in profile clicks compared to specification 1. The identification concern was that _E_ ( _For ei_ ) = 0 leading to biased estimates of _β_ 2. Comparing how much coefficient _β_ 2 changes as one reduces the error term by controlling for _zi_ provides an indication to what extent initial results suffered from omitted variable bias. Estimating (1) and (2) separately and testing for equal coefficients, I cannot reject that the coefficients are identical (p-value: 0.52, results not reported). This supports the validity of identification strategy (1), although it is of course still possible that _E_ ( _For vi_ ) = 0.

# **4.2 Identification from Applicant Pool Composition**

## **4.2.1 Framework**

One common criticism of audit studies is that they cannot provide information on the effect of employer discrimination in equilibrium (Heckman (1998)). If the share of discriminating firms is small relative to the share of the minority, than the differences in callback rates observed in these studies may only have a muted effect in equilibrium. As observed by Arrow (1973), it is the attitude of the _marginal_ employer that may determine first order effects of discrimination. Charles and Guryan (2008) attempt to test the effect of discrimination on the marginal by measuring regional racist sentiments with data from the General Social Survey.

In order to derive predictions on the role of the applicant pool composition in determining the cost and prevalence of discrimination, I propose a simple framework in which the employer hires the applicant with the highest expected productivity. This framework builds on tournament models 14
“settlements” provided by the State Statistics Committee (SSC), which yielded a nearly exact match at the province level. All data collection efforts were carried out within the framework of the mahallas randomly selected in the first stage. The SSC was consulted in the design of the study, including the questionnaires used and regarding the sample design. Review and design support were provided by a panel formed of local think tanks and government representatives. Survey data collection was conducted by a private firm under the supervision of World Bank staff.

The administrative data collection approach was simple data entry from official mahalla records in selected PSUs. Each mahalla in Uzbekistan is legally obligated to maintain such records for every person and family residing in that location. These data cover the total population size, demographics, social protection programs, local amenities, and migrant populations. Following the conclusion of the survey data collection fieldwork, the survey data design weights were adjusted on observed population totals in the administration records within the mahallas. These estimates were assumed to be more accurate as they had been updated within three months of the time of the survey fieldwork.

The second stage procedure was conducted using simple random selection of households with equal probability within selected mahallas. A separate stratification level for households that receive social assistance was included, totaling four households per mahalla. The final target sample included 20 households per mahalla, 800 of which were social protection recipients by design. The baseline survey included a full consumption and expenditure module using a list/recall approach. The resulting estimates are representative for 12 regions (referred to as provinces in Uzbekistan), 1 autonomous republic, and 1 independent city (Tashkent), crossed with their urban areas (except for the City of Tashkent, which is entirely urban). The baseline survey was conducted entirely on tablet devices (CAPI), enabling validation using cross-referencing, confirmation using geo-coordinates, and other techniques to ensure accuracy. The survey was conducted over the course of a 1.5-month period in May/June 2018.

After completion of the face-to-face baseline, interviewers began regularly calling a randomly selected panel of 1,503-1,550 households over the phone to conduct short interviews, following a set monthly schedule agreed to by the participating households. The questionnaire for these phone interviews was designed to monitor views on reform related topics, trends in migration, subjective well-being, measures of income, employment, service disruptions, and related indicators. Phone-based interviews began on September 5, 2018, and the first 12 rounds of the survey are used in the analysis that follows, 9
the crisis, did not change significantly. The regulation appeared to provide sufficient restrictions in the event of an upsurge in lending (Chart 19).

**Chart 19. New issuance of household mortgage loans by currency**

<!-- Start of picture text --> HUF Bn Per cent<br>200 100<br>Prudent Ban<br>Lending<br>180 90<br>160 80<br>140 70<br>120 60<br>100 50<br>80 40<br>60 30<br>40 20<br>20 10<br>0 0<br>HUF EUR CHF Proportion of FX loans in total gross flow<br>Jan-07 Mar-07 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10<br><!-- End of picture text --> Source: MNB.

- **5) Ban on foreign currency mortgage lending:** Despite the success of the regulation aimed at facilitating prudent lending, in mid-August 2010 a law came into effect prohibiting registering a mortgage on real estate in the Land Register if it is based on a mortgage loan contract in foreign currency by natural persons. The effect of this act was rather negligible, given that foreign currency mortgage loans had practically disappeared already on the back of the act on prudent lending.

- **6) Enhancement of the mortgage bond market:** As the study by the Csajbók et al. (2010) demonstrated, the lack of availability of long-term, fixed-interest-rate loans in domestic currency reduces the possibility of an upsurge in foreign currency lending. This requires long-term forint savings. In addition, the crisis proved that a reason for the vulnerability of the Hungarian economy is the lack of long-term forint savings. With that in mind the central bank took steps to enhance the forint-denominated mortgage bond market. In this context it launched a mortgage bond purchase program with the intention of purchasing mortgage bonds in the primary and secondary markets at a value of HUF 100 billion at most. With these steps the MNB wanted to improve the covered bond market which may have positive effects on the demand of these securities.

- **7) A proposal package aimed at reducing banks’ abuse of dominant economic position for the protection of distressed customers:** The package adopted at the end of 2010 increased the rights of borrowers in certain aspects while it strived to improve the transparency of pricing; however, it failed to achieve real changes. The points accepted include the following:

24
If the equilibrium changed from “Not use CC—Not report” to “Use CC—Report” with TIETP, except for expensive transactions with collusion between business and end‐consumers, TIETP might contribute to reducing the shadow economy. According to Jang’s survey (1997), conducted before TIETP’s introduction, while only 8.9 percent of survey respondents definitely obtained receipts in retail stores, approximately 90 percent<sup>39</sup> answered that they would pay with a credit card if the government introduced tax deductions for credit card payments. Another survey’s results showed that 75.8 percent of respondents would use credit cards more frequently if tax incentives for their use were introduced.<sup>40</sup>

# 5. TIETP Incentive Structures

In 1999, the MOFE designed TIETP to encourage people to use credit cards but at the same time to limit the fiscal impact of the policy. TIETP offered tax deductions only from taxable labor income. It did not allow tax deductions from business income, real‐estate rent income, or forest income, since expenses related to those incomes were already tax deductible under the Income Tax Law. The credit card tax deduction was limited at both ends by a minimum threshold and a maximum ceiling, and it also included a sunset clause. Until 2002, eligible income deductions (EID) were allowed at the 10 percent (deduction rate) of electronically traceable payments (ETP), including credit card or debit card payments exceeding 10 percent of total labor income (TLI) in a taxable year, within the ceiling set at the lesser of three million won (approximately US$2,600) or 10 percent of TLI.<sup>41</sup> To avoid double deductions, insurance premiums paid to public insurance funds, including National Health Insurance, National Employment Insurance, and National Pension Fund, and for commercial indemnity insurance, as well as tuition and entrance fees paid to public and private regular educational institutions, were not included in eligible ETP.<sup>42</sup> In addition, the following areas, for which underreporting was not a problem, were also not included in eligible ETP: national and local taxes; utility payments, including electricity, water, telephone, television, heating and cooking fuel gas, and so on; and transactions abroad.<sup>43</sup> However, medical expenses, tax deductible if in excess of the deduction threshold under the

> 39. Use credit card without exception (56%), transact only with credit card member stores (5%), use credit card even for the payment of small amounts (26%), less interest (10%), no interest (2%), no response (1%).

> 40. “More Use of Credit Cards If Tax Incentive for Credit Card Use Were Introduced: Samsung Card’s Survey to 300 Customers,” _Kyunghyang Shinmun,_ July 19, 1999.

> 41. Article 126‐2, Preferential Tax Control Law, effective as of August 31, 1999.

> 42. Article 121‐2, Presidential Decree of Preferential Tax Control Law, effective as of October 30, 1999.

> 43. Ibid.

25
- 60 -

83. Embart CB, Morrow-TlucalrM, Marler MR, Wolf AW (1987) Low level lead exposure in the prenatal and early preschool periods: early preschooL development. Neurotoxicol Teratol 9;259270.

84. Vimpani GV, Wigg NR, Robertson EF, McMichael AJ, Baghurst PA, Roberts RJ (1985) The Port Pirie Cohort study: blood lead concentration and childhood developrental assessment. In: Goldwater UJ, Wysocki LM. Volpe _RA_ eds. Edited proceedings: Lead environmental health ^ the current issues; May, Durham, NC,: Duke University; 139-146.

85. Needleman H and Gatsonis C (1990) Low-level lead exposure and the IQ of children: A metaanalysis of modem studies. JAMA 263:673-678.

86. Fulton M, Raab G, Thomson G et al. (1987) Influence of blood lead on the ability and attainment of children in Edinburgh. Incet 1:1221.

87. Hatzakis A, Kokevi A, Katsouyanni K (1987) Psychometric intelligence and attentional performance deficits in lead exposed children. In: International Conference on Heavy Metals in the Ervironment. Edinburgh, Scotdand:CEP Consultants. 204.

88. Hawk B, Scbroeder S, Robinson G e al. (1986) Relation of lead and social factors to IQ of low SES children A partial replication. Am J Ment Def 91:178-193.

89. Landsdown R, Yule W, Urbanowicz M et al. (1986) The relationship between blood-ead concentrations, intligence attainment and behavior in a school population: The second London study. Tnt Arch Occup Environ Health 57:225-35.

90. Schroeder S, Hawk B, Oto D et al. (1985) Separating the effects of lead and social factors on IQ. Environ Res 91:178-83.

91. Yule W. Lansdown R, Millar I a al. (1981) The relationship between blood lead concentration, intelligence and attainment in a school population; A pilot study. Dev Med Child Neurol 23:567576.

92. Centers for Dlisease Control (199 1) Strategic Plan for the Elimination of Childhood Lead Poisoning. U.S. Department of Health and Human Services, February.

93. Winneke G (1990) Results from the European multicenter study on lead neurotoxicity in children: Implications for risk assessment Neurotox and Teratology 12:553-559.

94. Achmadi UF,<sup>t</sup> The socioenvironmental factors and the acute respiratory infection episode among children under five, in Jakarta, prcsented at the Intemational Interdisciplinary Conference on Children at Risk, Bergen, Norway, May 1992.

_95._ Ministry of Health, 1986 Household Health Survey.

96. Ministry of Health, Health Ecology Research Center, 1991.

97. Budhy Djayanto, Prevalensi asma pada anak di sekolah dasar, Ph.D. thesis, University of Indonesia, 1991).
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# Amaru IV Cooperative 1980

The once and future resource managers WWF-US, Unpubl. 120p Andujar, Claudia 1986 Brazil: why an intervention against the invasion of Yamomani territory and the creation of their park is urgent.

IWGIA Newsletter; 45, 29-34 Annis, Sheldon 1987 Reorganization at the grassroots Grassroots Development; 11(2) 21-25 Apin, Theresa 1987 The Sarawak timber blockade Ecologist; 17 (4/5) 187-8 Baines, Graham (ed) 1984a Newletter on the Commisssion on Ecology's Working Group on Traditional Knowledge, Conservation and Rural Development, No 1. IUCN, Gland, Switzerland

# Baines, Graham 1984b

Environment and resources - managing the South Pacific's future Ambio; 13 355-8

# Batisse, Michel 1986

Developing and focusing the biosphere reserve concept UNESCO Nature end Resources; 22 (3) llp Belous, P 1976 Subsistence uses in new national park areas in Alaska US Nat. Pk. Serv. Unpubl. 14p Bernhardson, Wayne 1986 Campesinos and conservation in the Central Andes: indigenous herding and conservation of the vicuna Ambio; 13 (4) 311-8 Berreman, Gerald D 1979 Himachal: science, people and "progress" IWGIA Doct. 36 43p Best, Stephen 1986 The animal rights viewpoint Symp. Alberta Scc. Prof. Biol. : Native People and Resource Management. Proc; 197-213
Table A.1 Determinants of Land Cotton Shares

||1997|1998|1999|2000|2001|2002|
|---|---|---|---|---|---|---|
|Age of household head|_−_1_._00|_−_0_._21|_−_0_._86|_−_0_._45|_−_0_._08|_−_0_._68|
||0.51|0.57|0.51|0.70|0.56|0.49|
|Age squared|0.004|_−_0_._003|0.004|_−_0_._001|_−_0_._004|0.0006|
||0.005|0.006|0.005|0.007|0.006|0.005|
|Family size|2.53|4.77|0.01|0.26|_−_4_._87|2.37|
||2.42|2.72|2.62|3.11|2.70|2.49|
|Male household head|9.79|10.70|6.59|5.87|11.54|7.90|
||3.56|3.88|3.69|4.45|3.76|3.04|
|Share of males|18.02|11.72|12.87|_−_0_._11|6.13|_−_9_._04|
||6.82|7.47|7.41|8.76|7.02|6.42|
|Total land|29.30|33.07|34.51|34.20|31.69|23.53|
||2.11|2.40|2.51|3.35|2.43|1.94|
|Farm type|1.26|_−_0_._63|3.06|23.41|4.32|_−_0_._27|
||3.03|3.82|3.80|5.41|3.45|3.10|
|Livestock|_−_1_._67|3.61|6.64|9.33|3.80|3.18|
||2.71|2.99|3.07|3.59|3.05|2.80|
|Value of harrows|0.36|3.09|2.72|1.00|-|1.73|
||2.51|2.40|1.65|2.53|-|1.39|
|Value of ploughs|_−_2_._04|_−_4_._32|_−_3_._15|0.21|-|0.43|
||1.11|1.05|0.84|0.74|-|0.57|
|Constant|_−_28_._43|_−_59_._26|_−_51_._40|_−_82_._93|_−_51_._00|_−_21_._36|
||14.01|15.52|14.50|18.43|15.43|13.57|

Tobit estimates of land cotton shares. Includes dummy district variables. A separate regression is run in each year to account to macro shocks, prices, and the reforms. Since no information on assets was collected in 2001, the Tobit specification for that year does not include the value of harrows and the value of ploughs.

38