rafmacalaba/datause-encoder-data huggingface dataset:
19 information about scarcity, and fails to take account of the difficulties of making the price system work. At the same time, the standard theory fails to recognize some central virtues of the market – its ability to address problems of selection, incentives, information gathering, and innovation – because the standard paradigm is silent about all these problems.

Compared to the state of economics in 1970, mainstream theory can now accommodate a far broader ranger of phenomena. But there is no unified single framework, as there was in the Walrasian paradigm. Instead, there is a fragmented collection of disparate models. Distinct models are capable of explaining the same phenomena but are difficult to distinguish empirically.

A further problem that remains for future work is that multiple forms of private information exist within any sector. With multiple incentive problems, it is necessary to consider the distortions that result when incentives for more easily observed actions are created at the expense of less easily observed actions.

In these ways, Stiglitz’s theoretical work has contributed to the resurgence of empirical work in economics. Kim, Morse and Zingales (2006) document a reversal in the previous 30 years in the importance of theoretical work, which dominated the profession in the 1970s and 1980s, and gave way to the primacy of empirical work in the early 1990s. Much of that empirical work is a response to a body of theory that established that neither markets nor governments work perfectly. Stiglitz’s demonstration that imperfect information undermines the results of the standard neoclassical model has shifted not only models of thought in economics, but also the relative importance of different sources of knowledge about the economy.

# **Selected works**

1970. (With M. Rothschild.) Increasing risk: I. A definition. _Journal of Economic Theory_ 2, 225–43.

1971. (With M. Rothschild.) Increasing risk: II. Its economic consequences. _Journal of Economic Theory_ 3, 66–84.

1974. Incentives and risk sharing in sharecropping. _Review of Economic Studies_ 41, 219–55.
<!-- Start of picture text --> A. Quantiles of Permanent Transfers and Growth B. 2008Q2 Stimulus Payments (WL)<br>OK<br>41<br>50<br>WV<br>1 2 3 6789101112 4042434445464748 49Line slope=1.9[t-stat=2.8] CTMA NJCACOMDMNVAILWYWAAKDENHUTNDHINEKSPARIIAORTXWIAZVTMOOHMIINGANCMETNIDFLKYMTNMLA SC ARLine slope=0.28 [t=2.02]AL MS<br>NY SD<br>5<br>4 NV<br>-0.4 -0.2 0.0 0.2 0.4 2 3 4 5 6 7<br>Permanent Social Security Transfers (% of labor income) Transfer stimulus payments, % of labor income (2008Q2)<br>C. 2008Q2 Stimulus Payments (and GDP) D. 2001Q3 EGTRRA Stimulus Payments<br>OK NM<br>DE LAHI WY<br>CT MACANJDENY WA CO MDMNNVILVAUTHIORTXNENHNDIAAZRIKSSD PA WIINOHNCVTMOGAFLLAMIIDNMMETNMTKY SCWVARLine slope=0.9AL [t=2.53] MS NYCTCAMATXCONJGAILAKNVVAWAMNUTNCTNMDMIOHORAZMONEOKPAKSALNHSDFLRISCIDINMSWIARKYIAVTND ME MTWVLine slope=1.26 [t=4.03]<br>1.5 2 2.5 3 3.5 4 4.5 1.5 2 2.5 3 3.5<br>Transfer stimulus payments , % of state GDP (2008Q2) Transfer stimulus payments, % of labor income (2001Q3)<br>0.8 2<br>0.4<br>0<br>0.0<br>-2<br>-0.4<br>-0.8 -4<br>Quarterly Growth in Real Labor Income PC (%) Growth in labor income per capita, 2008Q2 (%)<br>2<br>4<br>1<br>2<br>0<br>0 -1<br>-2<br>-2<br>-3<br>Growth in state GDP per capita, 2008Q2 (%)<br>Growth in labor income per capita, 2001Q3 (%)<br><!-- End of picture text --> Notes: Panel A: Each point is the mean growth rate residual or mean Social Security increase residual (share of labor income) of 50 quantiles (controlling for state and time FEs). Quantiles with tiny transfer residuals are not shown. Panels BD: each point in the scatter plot is the growth in per-capita labor income or GDP per capita (GDPPC) (y-axis) in the quarter, plotted against the size of the contemporaneous transfer (x-axis). Sources: BEA, Romer and Romer (2016).

Figure 1. Scatter Plots: Transfers and Economic Growth signicant at the 1% level. This relationship is not driven by a couple of bins: an outlier-robust regression generates a similar slope and t-statistic.

For temporary transfers, the line slope ranges from 0.31.2, depending on the quarter and income variable, and the scatter plots help us to understand the drivers of cross-state variation in transfers. Figure 2 Panel B plots 2008 transfers (share of labor income) against growth, which have a relative multiplier (line slope) of about 0.28 (t-stat = 2.0)remarkably similar to the pooled temporary transfer multiplier estimated later in regressions. The cross-state variation in transfers is striking: The 2008 ESP ranges from around 2.3% of 15
- Zhu, G., Wang, L., Zhang, P., Song, K., 2016. A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors:. International Journal of Distributed Sensor Networks 2016, 1–11. doi:10.1155/2016/ 9043835.

- Zitzler, E., Laumanns, M., Bleuler, S., 2004. A Tutorial on Evolutionary Multiobjective Optimization, in: Gandibleux, X., Sevaux, M., S ̈orensen, K., T’kindt, V. (Eds.), Metaheuristics for Multiobjective Optimisation, Springer Berlin, Heidelberg. pp. 3–37.

- Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C., da Fonseca, V., 2003. Performance assessment of multiobjective optimizers: an analysis and review. IEEE Transactions on Evolutionary Computation 7, 117–132. doi:10.1109/TEVC.2003.810758.

50
Information instruments have diverse forms, including reports of measured pollution, environmental accident reports, and environmental performance ratings. In the US, for example, the Toxic Release Inventory (TRI) discloses toxic chemical releases and waste management activities by significant toxic polluters and federal facilities. In developing countries, however, weak regulatory institutions may have much greater difficulty in implementing such emissions inventories. In addition, despite an emerging literature on stakeholders’ role in improving firms’ environmental performance (Arora and Cason, 1998; Blackman and Bannister, 1998; Pargal and Wheeler, 1996; Wheeler et al., 1997), concerns remain about the public’s ability to understand and utilize complex emissions reports. For example, Bui and Mayer (2003) find that the release of TRI’s highly-detailed information on facilities’ toxic emissions has virtually no effect on housing prices in neighboring areas, even when the release is unexpected. The dual problems of emissions inventories in developing countries – technical feasibility and public understanding – have led to a preference for programs that condense complex information into environmental performance ratings that are disclosed to the public.

Research on the effectiveness of performance rating and disclosure (PRD) programs suggests that that have a significant, positive impact on regulatory compliance (Afash et al., 1997; Dasgupta et al., 2006; Garcia et al., 2007, 2009; Wang et al., 2004). Dasgupta et al. (2006) summarize the changes in compliance rates for several PRD programs in Asia: One and two years after the inception of a PRD, compliance rates increased from 37% to 61% in Indonesia, 8% to 58% in the Philippines, 10% to 24% in Vietnam, 75% to 85% in Zhenjiang, China and 23% to 62% in Hohhot, China.

Several empirical studies also find that PRD programs have improved firms’ environmental performance in Indonesia (Afash et al., 1997; Garcia et al., 2007, 2009) and China (Wang et al., 5
in the policy experiment, in which more data was collected from beneficiaries’ households. Data was only collected on a subset of common off-farm businesses types. “HH” stands for household.<sup>†</sup> p<.10, *p<.05, **p<.01, ***p<.001.

**Table S9.** Results of mediation analysis of the effects of Personal Initiative and Interpersonal Initiative interventions on the economic composite index through psychosocial variables at <u>endline in the Mechanism Experiment</u>

|**Mediator Variable**|**‘a’ path**<br>**(SE)**|**‘b’ path**<br>**(SE)**|**Indirect Effect**<br>**(95% CI)**|
|---|---|---|---|
|Personal Initi<br>|ative condition<br>|vs Controlconditio<br>|n(N=1,840)<br>|
|Psychosocial composite index|0.10*<br>(0.05)|0.40***<br>(0.02)|0.04*<br>(95% CI 0.00 to 0.07)|
|Intrapersonal composite index|0.13**<br>(0.05)|0.40***<br>(0.02)|0.05**<br>(95% CI 0.01 to 0.09)|
|Relational composite index|0.05<br>(0.05)|0.32***<br>(0.02)|0.01<br>(95% CI -0.01 to 0.04)|
|Future expectations|0.12*<br>(0.05)|0.32***<br>(0.02)|0.04*<br>(95% CI 0.01 to 0.07)|
|Well-being|0.09*<br>(0.05)|0.24***<br>(0.02)|0.02<sup>†</sup><br>(95% CI 0.00 to 0.04)|
|Household Dynamics|0.03<br>(0.05)|0.19***<br>(0.02)|0.00<br>(95% CI -0.01 to 0.02)|
|Interpersonal In<br>|itiative conditio<br>|n vs Control condi<br>|<br>tion(N=1,854)<br>|
|Psychosocial composite index|0.12<br>(0.05)|0.38***<br>(0.02)|0.05**<br>(95% CI 0.01 to 0.08)|
|Intrapersonal composite index|0.12<br>(0.04)|0.38***<br>(0.02)|0.04*<br>(95% CI 0.01 to 0.07)|
|Relational composite index|0.09<sup>†</sup><br>(0.05)|0.29***<br>(0.02)|0.03*<br>(95% CI 0.00 to 0.06)|
|Future expectations|0.15**<br>(0.05)|0.30***<br>(0.02)|0.04***<br>(95% CI 0.01 to 0.07)|
|Well-being|0.08<sup>†</sup><br>(0.05)|0.20***<br>(0.02)|0.02<sup>†</sup><br>(95% CI 0.00 to 0.03)|
|Household Dynamics|0.10<br>(0.04)|0.17***<br>(0.02)|0.02*<br>(95% CI 0.00 to 0.04)|

Note: Only those psychosocial variables that showed significant ‘a’ paths, i.e., positive treatment effects by one or both interventions are included in this table (‘a’ path reflects results from Table 2). The ‘mediation’ package in R was used with 1000 bootstrapped simulations to generate the indirect effect and its 95%CI. The ‘b’ paths were estimated with robust SEs. All mediator variables are standardized. All analyses control for policy experiment treatment arm, timing of the policy experiment activities by season, and participation in the policy experiment baseline survey. N=122 observations were dropped due to missing data on one or more of the mediator variables in the Personal Initiative vs Control condition analysis and N=108 observations in the Interpersonal Initiative vs Control condition analysis.<sup>†</sup> p<.10, *p<.05, **p<.01, ***p<.001.

51
fiscal policy are greater than in advanced economies (Aizeman and Jinjarak 2010). However, the cumulative (multi-period) multipliers tend to be smaller for emerging markets than for advanced economies as the positive impact of an increase in government expenditures on GDP tends to fall off quickly (Ilzetki, Mendoza, and Vegh, 2011). Also, the size of public spending multipliers tends to be much smaller (zero or even negative) in highly indebted countries due to crowding out of private investment.

Source: Fardoust, Lin and Luo (2012), and review of literature by authors.

Some researchers find that expenditure on infrastructure investment and transfers targeted at the poor have the largest fiscal multipliers among all categories of government spending (Horton, Kumar, and Mauro 2009). Other researchers point to the inherently medium- to longer- term nature of infrastructure investments. Implementation takes time, and due processes need to be followed in appraising and selecting investment projects.

Government revenues at all levels generally follow a procyclical pattern: they automatically grow faster during economic upswings and slower during downturns. For a particular subnational government, revenue growth depends on both (a) its own tax revenue base, related to GDP within its region, and (b) the transfer of resources from the central government, in the form of a share of central taxes, central grants, or both.

The distribution and timing of the impact of the economic slowdown on revenues depends on the division of taxing powers between the levels of government. In countries where states/provinces rely mainly on their own revenues (for example, the United States), subnational government revenues could vary because of differences in regional economic growth. Where subnational governments rely largely on central transfers (for example, Mexico), the revenue impact is more uniform across regions. In this case, subnational government revenues are driven mainly by GDP at the national level and its impact on central revenues.

The situation is more complicated when there is large variation across subnational governments within a country in terms of their dependence on central transfers (for example, Brazil, India, and to a lesser extent, China). In the countries of the Organization for Economic Co-operation and Development (OECD), subnational government revenues react 8
Ende (2009). Rapid malaria diagnostic tests vs. clinical management of malaria in rural Burkina Faso: safety and effect on clinical decisions. A randomized trial. _Tropical Medicine & International Health 14_ (5), 491–498.

- Brownlee, S., K. Chalkidou, J. Doust, A. G. Elshaug, P. Glasziou, I. Heath, S. Nagpal, V. Saini, D. Srivastava, K. Chalmers, et al. (2017). Evidence for overuse of medical services around the world. _The Lancet 390_ (10090), 156–168.

- Busfield, J. (2015). Assessing the overuse of medicines. _Social science & medicine 131_ , 199–206.

- Chandra, A., A. Finkelstein, A. Sacarny, and C. Syverson (2016). Health care exceptionalism? Performance and allocation in the US health care sector. _American Economic Review 106_ (8), 2110–44.

- Cissoko, M., M. Magassa, V. Sanogo, A. Ouologuem, L. Sangaré, M. Diarra, C. S. Bationo, M. Dolo, M. D. Bah, S. Doumbia, et al. (2022). Stratification at the health district level for targeting malaria control interventions in Mali. _Scientific reports 12_ (1), 1–17.

- Cohen, J., P. Dupas, and S. Schaner (2015). Price subsidies, diagnostic tests, and targeting of malaria treatment: Evidence from a randomized controlled trial. _American Economic Review 105_ (2), 609–45.

- Currie, J., W. Lin, and J. Meng (2014). Addressing Antibiotic Abuse in China: An Experimental Audit Study. _Journal of Development Economics 110_ , 39–51.

- Das, J. and J. Hammer (2014). Quality of primary care in low-income countries: Facts and economics. _6_ , 525–553.

- Das, J., J. Hammer, and K. Leonard (2008). The Quality of Medical Advice in Low-Income Countries. _The Journal of Economic Perspectives 22_ (2), pp. 93–114.

- Das, J., A. Holla, A. Mohpal, and K. Muralidharan (2016). Quality and Accountability in Health Care Delivery: Audit-Study Evidence from Primary Care in India. _American Economic Review 106_ (12), 3765–99.

- de Chaisemartin, C. and J. Ramirez-Cuellar (2024). At What Level Should one Cluster Standard Errors in Paired Experiments, and in Stratified Experiments with Small Strata? _American Econonmic Journal: Applied Economics 16_ (1), 193–212.

- de Walque, D., E. Kandpal, A. Wagstaff, J. Friedman, M. Piatti-Fünfkirchen, A. Sautmann, G. Shapira, and E. Van de Poel (2022). _Improving Effective Coverage in Health: Do Financial Incentives Work?_ World Bank Publications.

- Djimde, A. A., H. Maiga, I. Sagara, K. Traore, H. Niangaly, A. Bamadio, A. Grivoyannis, M. Tekete, O. B. Traore, A. Kodio, et al. (2016). Field Assessment of SD Bioline Malaria Species Antigen Detection by Rapid Diagnostic Tests in Mali. _Journal of Parasitology and Vector Biology 8_ (1), 1–9.

24
Meeting of the American Anthropological Association, November 20, 1958, Washington D.C.) Caribbean Studies 1(2) 1961:1-5.

Jamaica, Ministry of Health. "Perinatal Mortality and Morbidity Survey" Report of the Preliminary Findrings, Dec. 1987.

Jamaica, Ministry of Health. "The Perinatal Mortality and Morbidity Survey, Jamaica." Final Report, July 1989.

Jamaica, National Family Planing Board. "Report of the Jamaica Contraceptive Prevalence Survey:1983. " August, 1984.

Jamaica, National Family Planning Board. "Young Adult Reproductive Health Survey, Jamaica, 1987." Preliminary Report, Sept. 1987.

Jelliffe, DB "Child Nutrition in Developing Regions" US Government Publication No. 1822. Washington DC: US Govt. Printing Office, 1968. Leslie, J & Gupta, G. "Utilization of Formal Services for Maternal Nutrition and Health Care." Washington, DC: International Center for Research on Wbmen, 1989.

Lettenmaier et al., '"Mthers' Lives Matter: Maternal Health in the Qiimumity." Population Reports Series L, No 7; 16(2) 1988.

Iewis, Maureen. "Financing Health Care in Jamaica." The Urban Institute, Washington DC, Nov, 1988. Rept # 3714-04. (DRAFT) lewis, Maureen. "Government Policy and the Effectiveness of User Charges in Jamaican Hospitals. " The Urban Institute, Washington, D.C., March, 1989. Rept 3714-05. (DRAFT) ITofgren, 0 & Polberger, S. "Perinatal Mortality: Changes in the Diagnostic Panorama, 1974-1980." Acta Paediatrics Scand 72 1983:327-332.

Long, Joseph K. "Jamaican Medicine: Choices between Folk Healing and Modern Medicine." Unpubl., PhD dissertation, University of North Carolina, 1973. MacCormack, C.P. "Lay Concepts Affecting Utilization of Family Planning Servioes in Jamaica." J of Tropical Medicine & HMgiene 88(4) 1985:281-285.

Maine, D. Family PlanninW: Its ImPact on the Health of Women and Children New York: Columbia Ctr for Pcpulation & family Health, 1981.

Marchione, Thomas J. "Evaluating Primary Health Care and Nutrition Programs in the Context of National Development." Social Science & Medicine 19(3) 1984:225-235.

McNeil, Pamela; Olafson, Freya; Powell, Dorian L; and Jackson, Jean. "TIhe Women's Centre in Jamaica: An Innovative Project for Adolescent Mothers." Studies in Family Plannirm 14(5) 1983:143-149.

25
|0.256<br>9.828|
|---|

# Adj. R2 0.256 Mean of the dependent variable 9.828 **Dependent Variable: Sensitivity analysis: LN Total cost of tax compliance (+10% across the board)**

||Coeff.|Std.<br>Error|Sig.|
|---|---|---|---|
|(Constant)|6.342|0.287|0.0%|
|LN full-time employees|0.146|0.029|0.0%|
|LN of q55 after imputed values were introduced (imputed "no answer")|0.209|0.022|0.0%|
|Share of activities completely outsourced|0.075|0.086|38.4%|
|Share of activities partially outsourced|0.679|0.105|0.0%|
|Adj. R2|0.256|||
|Mean of the dependent variable|9.766|||
|**Dependent Variable: LN of total cost of tax compliance**|Coeff.|Std.<br>Error|Sig.|
|(Constant)|6.240|0.287|0.0%|
|LN full-time employees|0.147|0.029|0.0%|
|LN of q55 after imputed values were introduced (imputed "no answer")|0.210|0.022|0.0%|
|Share of activities completely outsourced|0.154|0.086|7.5%|
|Share of activities partially outsourced|0.721|0.105|0.0%|
|Adj. R2|0.256|||
|Mean of the dependent variable|9.699|||

|**Dependent Variable: Sensitivity analysis: LN Total cost of tax complianc**<br>**board)**|**e (-10% across**|**the**||
|---|---|---|---|
||Coeff.|Std.<br>Error|Sig.|
|(Constant)|6.126|0.287|0.0%|
|LN full-time employees|0.148|0.029|0.0%|
|LN of q55 after imputed values were introduced (imputed "no answer")|0.211|0.022|0.0%|
|Share of activities completely outsourced|0.242|0.086|0.5%|
|Share of activities partially outsourced|0.770|0.105|0.0%|
|Adj. R2|0.258|||
|Mean of the dependent variable|9.626|||

|**Dependent Variable: Sensitivity analysis: LN Total cost of tax compliance**<br>|**(-20% across**|**the**||
|---|---|---|---|
|**board)**||||
||Coeff.|Std.<br>Error|Sig.|
|(Constant)|5.999|0.288|0.0%|
|LN full-time employees|0.148|0.029|0.0%|
|LN of q55 after imputed values were introduced (imputed "no answer")|0.212|0.022|0.0%|
|Share of activities completely outsourced|0.342|0.087|0.0%|
|Share of activities partially outsourced|0.827|0.105|0.0%|

35
Efficiency and competitiveness require eliminating redundant jobs. As part of the restructuring and privatization process, many utilities in the DTEs implemented labor rationalization programs that led to substantial shedding of excess employment. It is important to note that in South Africa, there was an over 50 percent reduction in the number of workers employed by the publicly owned electricity utility Eskom from over 66,000 in 1985 to 32,800 in 2000 (and a further reduction of 17 percent from 2000 to 2003).<sup>46</sup> These reductions led to dramatic increases in labor productivity since they were taking place while Eskom was experiencing a robust growth in sales. Labor productivity in South Africa’s electricity supply industry, as measured by sales per employee, more doubled between 1996 and 2004 (figure 13).

**Figure 13  Eskom’s sales per employee (GWh/employee)**

<!-- Start of picture text --> 8<br>7<br>6<br>5<br>4<br>3<br>96 97 98 99 00 01 02 03 04*<br>year<br>GWh per employee<br><!-- End of picture text -->

* The figure refers to the 15-month period from 1 January 2004 to 31 March 2005 _Source_ : Eskom Annual Report (various years).

The above increases in the labor productivity of the electricity supply industry were obtained during a period when South Africa registered only very modest overall labor productivity growth, falling behind many other African economies and raising serious concerns about the country’s eroding competitive position. Indeed, during 19952002, South Africa’s labor productivity growth was low and lagged all but the South American economies in its income group (figure 14).

Despite the impressive gains in labor productivity of recent years, Eskom still ranks well below many systems from the advanced industrial countries (figure 15).

> 46 Eberhard and Mtepa (2004), _ibid_ .

29
59 5. The pairs of similar firm names identified in Step 4 are then sorted alphabetically to identify neighbor names (i.e., names that appear in consecutive rows after sorting) and correct any potential similarities that may have been missed in Step 4.

6. The algorithms in Step 4 generate “big groups” of firm names that are considered similar because they share several common words. To break up these “big groups”, firm names are sorted alphabetically within each group and, if two consecutive firm names do not have sufficiently similar pre-processed names (as captured by a cutoff in the Levenshtein distance), the group is “broken” at that place, resulting in two separate groups of similar firm names.

7. After similar firm names are identified from the steps above and assigned temporary unique numeric identifiers, firm names are then sorted alphabetically and based on firm address. If two consecutive names have similar addresses and similar names and did not have the same unique numeric identifier, they are joined in a new final unique numeric identifier.

The steps above are applied to clean the names of Sri Lankan firms. A large number of transactions, especially in the import data, are made by firms whose names indicate they are courier companies. Since these transactions are made for a third party, frequently individuals, and since their total trade value is negligible, we dropped all observations whose names are of courier firms.<sup>97</sup> Finally, we also drop from the sample observations for which the firm name corresponds to an individual making personal imports under a permit.<sup>98</sup> Such observations account for a very small total trade value.

# **A.C Agricultural Production, Cultivated Area, and Yields**

We rely on both administrative data and remote sensing estimates.

## **A.C.1 Administrative Data**

For rice, we obtain data on production and cultivated area in each district from the ‘Paddy Statistics’ produced by the DCS for each growing season from 2012-2013 Maha to 2022 Yala.<sup>99</sup> Crucially, this time frame includes the 2019-2020 Maha and 2020 Yala seasons, which we use as the pre-ban baseline to estimate the model in Section VI.B.

For non-rice, non-tea crops (maize, groundnuts, potatoes, onions, cinnamon, and cloves), we obtain data on production and cultivated area at the divisional secretariat (DS) level from the DCS for each growing season from Maha 2019-2020 to Yala 2022, which we aggregate up to the district level. For tea, the DCS data includes information on cultivated area but not on production, so we

> 97Namely: “dhl express parcel delivery”, “d h l”, “fits aviation”, “cargo logistics worldwide aramex courier freight” “non commercial xpress by air freight” “Skynet shipping setrans” “sky international”.

> 98Such firm names have the structure “Person Name+Institution+PERMIT”. For example: “KADAWARAGE C V WING COMMANDER (DENTAL DOCTOR) SRI LANKA AIR FORCE MIN.OF DEFENCE PERMIT”.

> 99Paddy Statistics were accessed at: http://www.statistics.gov.lk/Agriculture/StaticalInformation/Paddy ~~S~~ tatistics.