rafmacalaba/datause-encoder-data huggingface dataset:
governance institutions. Olken (2010) and Beath, Christia and Eniolopov (2012 _a_ ) studied the effects of the community choosing CDD projects by referendum compared to committees, which are susceptible to elite capture. Both studies found that villagers who were surveyed were more satisfied with the projects that were chosen by direct democracy, although there did not seem to be any difference in the types of projects chosen. Grossman (forthcoming) found that producers’ groups run by elected managers performed better than groups run by mangers chosen by elites. He attributes the difference to the superior monitoring institutions and auditing practices adopted by elected managers but not by mangers chosen by elites. These studies indicate that some of the disconnect between CDD programming and better outcomes may be due to elite capture of the project selection process and subsequent monitoring and auditing of the project. Gugerty and Kremer (2008) have similar findings in their study of women’s groups in Tanzania. The question remains whether CDD programs can increase participants’ preferences for pro-social activity and enhance social networks that should help incentivize that activity.

# **5 Measurement**

Social capital is a concept that raises special measurement difficulties. Often surveys are used in which respondents are effectively asked if they posses social capital (“Do you think people are generally trustworthy?”“Would ould you be willing to contribute to public good X?”) Program staff typically stress the importance of social capital in their interactions with members of the treated communities and, of course, they do not operate in the control communities at all. Thus respondents in treated communities may feel more compelled to give the “right” answer to questions than do control-community members, who may not even know what the “right” answer is since they have not received the training component of the program.

Therefore behavioral measures are more appealing, which is why Casey, Glennerster and 17
# **Exchange rates during the crisis**

Sebastian Weber Charles Wyplosz<sup>*</sup>

**Keywords:** Central Bank Policy, Exchange Rate Intervention, Competitive Devaluations, Financial Crisis **JEL Classification** : E58, E61, F33, F42

> * We thank Richard Newfarmer, Olivier Cattaneo and Patrick Messerlin as well as participants at WBCEPR conference “Trade Implications of Policy Responses to the Crisis” for helpful comments.
**Page** 8

**Livestock Insurance in Mongolia**

supplying individual insurance. Mongolia has unique characteristics that make these core problems even more challenging.

- / Multiple and complex weather conditions create the dzud. Actually documenting and understanding these events is important for risk mitigation and early warning efforts. However, after the fact the events are not as important as the outcome - extremely high livestock losses.

An attempt to construct a performance checklist will help the discussion. Table 1 makes this attempt and provides a subjective assessment for each of our three alternatives. These assessments are solely based on professional judgment and should not be taken as the final word. The table is provided as a quick guide to the reader so that they can more fully understand why this paper recommends the use of mortality index insurance.

|**Table**1:<br>**SubjectivePe**|**rformanceAssessm**|**entsforAlternat**|**ive Approaches**|
|---|---|---|---|
|**PerformanceGoals**|_Traditional_<br>_Insurance_|_Weather_<br>_Insurance_|_Mortality_<br>_Index_<br>_Insurance_|
|Insuranceshouldnot<br>rewardpoormanages|Fails|Pass|Pass|
|Affordabilityforpoor<br>herders|No|Couldbe|Couldbe|
|Effectiveriskprotection<br>forindividualherders|Forthemost<br>riskyyes|Insome<br>cases|Mostlikely|
|Focusedonthemost<br>significant covariantrisk|No|Couldbe|Likely|
|Sustainable&profitable<br>forprivate companies|Highly<br>unlikely|Possible|Possible|
|Fitswithotherformsof<br>emergencyaid|No|Possible|Possible|
|Low transaction costs|No|Shouldbe|Shouldbe|
|Acceptancefrom<br>intentional risksharing<br>markets|Notlikely|Shouldbe|Canbe|
|Opportunitiesforwell<br>definedrollsfor<br>governmentandmarkets|Withgreat<br>care|Possible|Possible|

It is clear that traditional approaches are scored the most poorly. A careful reading of Skees and Bamett will give more insights into the basis for that judgment. Traditional insurance scores best for providing specific protection to individual headers. However, in the current system the most risky herders who are in the most risky areas will receive this benefit since everyone is charged the same flat rate. These are precisely the wrong incentives given the desire to motivate herders to adopt risk mitigation methods. Further, if there were a large uptake in this insurance
new slots in which to fit and categorize people, _e.g._ the _perverted_ , the _suicidal_ , and the _heterosexual_ or _homosexual_ person, molds individuals’ sense of themselves and hence their behavior.

Of interest to us is here is how identity affects preferences over effort, the ability to learn, and the response to competitive environments. A standard view, which derives from Max Weber, is that culture—as a matter of self-conscious orientation or identity—imparts values that are consistent across situations. The values explain action. However, there is an alternative view, drawing on cognitive psychology, that culture is fragmented and contradictory: a given culture provides multiple frames, understandings, and worldviews, and they may not be consistent with one another. According to the sociologists Ann Swidler (1986, 2001) and Paul DiMaggio (1997), culture shapes behavior through frames that are _situationally_ evoked and that determine which actions seem possible and desirable _in that situation_ , given a person’s values. Background settings or contexts can alter motives and behavior by evoking a particular aspect of the self or a particular worldview and by altering the framework of meanings that help to constitute one’s social identity.

To test this hypothesis, we draw on our experiment in rural India that manipulates the salience and publicness of caste identity.<sup>1</sup> Under the traditional caste system, preeminence was assigned to birth rather than competition (Béteille, 2011, II[2003], p. 11): “For centuries it was believed that a man’s social capacities were known from the caste or the lineage into which he was born, and that _no further test was necessary to determine what these capacities were._ ” (p. 99, emphasis added) A body of work in anthropology supports the view that _individual_ mobility<sup>2</sup> was nearly impossible in the traditional caste system for someone who remained in or near his village,

> 1 Hoff and Pandey (2006) summarize the treatments that use only piece rate incentives ( _N_ =336) but do not present the treatments that use both piece rate and tournament incentives ( _N=_ 246).

> 2 As distinct from _collective_ mobility up or down the caste hierarchy.  The caste system is the product of politics and, thus, local political forces bring about changes in the local caste hierarchy and also in the number of distinct castes over the medium-  to long-term (Rao and Ban 2007).  In addition, when caste identity takes on significance for government incentives, some individuals are able to manipulate their official caste designation, but even this process is slow.  Thus Cassan (2011) estimates that over the course of 20 years, in response to British classification of some castes as “agricultural castes” whose members could own land, and others as “non-agricultural castes” whose members could not, 7.5% of the

3
Finally, figures 5.15 and 5.16 show the strong linear positive relation between the infrastructure contributions to the two components of the O&P decomposition based on TFP in logs and TFP in levels. Their corresponding coefficients of correlation are 0.69 and 0.77, respectively.

<!-- Start of picture text --> Figure 5.13. Cross-plot between Figure 5.14. Cross-plot between<br>demeaned aggregate productivity and demeaned aggregate productivity and<br>percentage absolute contributions of percentage absolute contributions of<br>infrastructure to allocative efficiency infrastructure to allocative efficiency via<br>(TFP in logs) simulations<br>2.5 2.5<br>2.0 2.0<br>1.5 1.5<br>1.0 1.0<br>R 2 = 0.1 R 2 = 0.24<br>0.5<br>0.5<br>0.0<br>0.0 0 10 20 30 40 50 60<br>0 10 20 30 40 50 Percentage Absolute Contribution of Infrastructure to Allocative<br>Percentage Absolute Contribution of Infrastructure to Allocative Efficiency via simulations<br>Efficiency (TFP in logs)<br>Figure 5.15. Cross-plot between Figure 5.16. Cross-plot between<br>percentage absolute contribution to percentage absolute contribution to<br>average log–productivity and allocative efficiency (with TFP in logs)<br>contributions via simulations and contributions via simulations<br>70 60<br>60 50<br>50<br>40<br>40<br>30<br>30<br>20 R 2 = 0.47 20<br>R 2 = 0.59<br>10 10<br>0<br>0 10 20 30 40 50 60 0<br>Percentage Absolute Contribution of Infrastructure to Average 0 10 20 30 40 50<br>Productivity via simulations Percentage Absolute Contribution of Infrastructure to Allocative<br>Efficiency via simulations<br>Demeaned Aggregate Productivity Demeaned Aggregate Productivity<br>Average log-Productivity<br>Percentage Absolute Contribution of Infrastruct Allocative Efficiency (TFP in logs)<br>Percentage Absolute Contribution of Infrastruct<br><!-- End of picture text --> Source: Authors’ calculations with IC data.

All effects of infrastructure are not supposed to be negative in all cases. There are positive factors intended to stimulate productivity and economic activity, such as the use of ICT or a firm’s own electricity generator. A question of interest is to what extent the impacts listed in table 5.1 are due to positive factors that enhance economic performance or negative factors that constrain economic activity. Since the absolute percentage contributions are constructed based on absolute values, at this point we still cannot say anything about the direction of the effect of infrastructure on economic performance. But it is easy to analyze the effect of the individual INF factors, and this is one of the aims of the following section.

41
**Table 2: Steps used to select papers in the systematic review**

|**Review**<br>**Phase**|**Procedures Used**|**Number of**<br>**Papers**|
|---|---|---|
|1|Google Scholar search|4,290|
|2|Review titles and eliminate irrelevant papers|434|
|3|Eliminate 23 duplicate papers|411|
|4|Review abstracts and conduct word search and remove<br>papers that do not seem to look at the impact of<br>income on consumption of temptation goods|232|
|5|Add 7 papers recommended by colleagues and 12<br>papers referenced in bibliographies of papers identified<br>in previous phases|251|
|6|Read papers and remove those without impact<br>estimates, level estimates, or qualitative reports of the<br>impact of cash transfers on consumption of temptation<br>goods|42|
|7|Categorize papers into 3 groups:||
||i) Papers with impact estimates|19|
||ii) Papers with level estimates|11|
||iii) Qualitative reports|12|

22
MENA interaction terms are added to the baseline equation (4) to capture differential regional effects.

Since the estimation of exporter size includes country-controls, some countries are excluded due to lack of a complete data profile. In estimation of equation (4), country coverage ranges from three countries with full country controls, to all countries without any country controls. In regressions with complete controls, only Morocco, Jordan and Egypt are represented. For the analysis of exporter size, data is at the country-sector-year level and additional variables are included in the regression to control for country level factors: the log of GDP per capita (PPP), trade openness and a tariff rate<sup>21</sup> (Table 7 in the Appendix). GDP can benchmark for market size. Country-level determinants included in the regression are the log of GDP per capita (PPP), trade openness, and a tariff rate. As a measure of trade openness, the total export and import value in manufacturing and services is divided by a country’s GDP ( _TradeOpen_ ) using data from the WDI.<sup>22</sup> The share of trade relative to GDP is similar in MENA and non-MENA regions, 0.79 and 0.78 respectively.

Results are examined when financial sector development is proxied as previously by the private credit to GDP ratio. Table 5 shows results where the complementarity between external finance dependence and private credit-GDP ratio is significantly and positively associated with both mean and median exporter size.

Comparing regions, financial impacts on export size are smaller in MENA when associated with _mean_ exporter size ( _Private Credit / GDP * MENA_ ). For a given sector, an identical increase in the private credit-GDP ratio yields a smaller increase in mean exporter size in MENA than in nonMENA countries.

However, large firms in MENA may be benefiting more from financial sector development than smaller firms. The interaction term _Private Credit/GDP*EXTFIN*MENA_ is positive in the case of _mean_ exports but not _median_ exports. This may illustrate a bias in access to finance depending on firm size. This is reasonable considering that large firms are favored by the financial sector in MENA but not significant to the same degree as in the rest of the world. MENA has the world’s highest loan concentration ratio, illustrating a bias in lending to large firms versus young and small firms (World Bank, 2011). Two more points on the size distribution are also examined, the 25th and 75th percentiles. Financial country-sector complementarities predict significantly larger increases in the 75th percentile of exporter size in MENA than non-MENA countries. There are no regional differences at the 25th percentile of exporter size. This is further evidence of gains from access to finance being reaped primarily by large firms in MENA. Further firm-level analysis would be interesting here to examine differences in access to finance by firm size.

> 21 Both average and weighted tariff rates were tested and yield very similar results. 22 This measure is constructed using constant 2000 USD and includes both manufacturing and service goods.

19
**Figure 1. Comparison between PACI and WB Corruption Control Index**

# A. PACI vs. WB-CCI

<!-- Start of picture text --> MW<br>ML<br>UGST<br>NP<br>KH<br>UZ<br>ZW<br>LR LY<br>MR<br>GQ CG<br>TDGNNG KZ DJTZMN GH<br>TMMM GENEZMMZ<br>BDHTCIKESDPKAZIQIDCMVEALRUPHAFBOECVNHNBYUAMKYEMGARDZGA B IRINRSRODOJA SNMACNEGBFSYHRSAPLPAPETRMXJMBRTHCUTTBGCOCRLVSVGRCZSKZAKWLTTNHUKRITMY BNJOBHQAUYTWSIOMPT ES JPBEIEFRUS DECALUNLUKATAUNOCHSESGDKFI<br>2 4 6 8 10<br>WB CC, year 2005<br>B. Log(PACI) vs. WB-CCI<br>MW<br>GQ ZWKHUZ LRCGLYSTUG NP MLMR<br>MMIQAFHTSDTMTDBD CINGCMPKGNKZAZKEVEBJBYIDZMYERUVNALBOHNECNESYUADJTZCNPHMNGAMZEGMKIRARDZSVJMINRSGEPAGHPEMAROBABRTHSABFTNTTSNTRBGMGHRPLLTMYBNOMCUJOLVGC R BHCZSKZAHUKW QASI UY LU<br>CO<br>DO KR AT<br>MX IT TW PT US NO<br>SG<br>FR<br>ES<br>BE DENL<br>JP IE CAUKAUSECH DKFI<br>-2 -1 0 1 2<br>WB CC, year 2005<br>8000<br>6000<br>PACI<br>4000<br>2000<br>0<br>10<br>8<br>6<br>Log PACI<br>4<br>2<br>0<br><!-- End of picture text --> _Notes_ : In Panel B, when the PACI equals zero (countries: FI, DK, IE, SE, AU, CH, CA), it has been set equal to arbitrary small numbers for the purpose of computing the log. Countries for which PACIz = 0 and Pr zero_ cases zPACI_ > 0.015 and countries for which PACIz > 10000 have been excluded.

19
|P117947|2012|2016|6/30/2016|10 Active|Colombia|
|---|---|---|---|---|---|
|P117947|2012|2017|1/23/2017|11 Active|Colombia|
|P117947|2012|2018|8/23/2017|12 Active|Colombia|
|P117947|2012|2018|3/9/2018|13 Active|Colombia|
|P117947|2012|2019|11/28/2018|14 Active|Colombia|
|P117947|2012|2019|5/3/2019|15 Active|Colombia|
|P117947|2012|2020|7/16/2019|16 Active|Colombia|
|P117947|2012|2020|2/7/2020|17 Active|Colombia|
|P117949|2010|2010|6/29/2010|1 Closed|Yemen,Republic of|
|P117949|2010|2011|12/26/2010|2 Closed|Yemen,Republic of|
|P117949|2010|2012|7/13/2011|3 Closed|Yemen,Republic of|
|P117949|2010|2012|11/29/2011|4 Closed|Yemen,Republic of|
|P117949|2010|2013|7/8/2012|5 Closed|Yemen,Republic of|
|P117949|2010|2013|2/11/2013|6 Closed|Yemen,Republic of|
|P117949|2010|2014|11/14/2013|7 Closed|Yemen,Republic of|
|P117949|2010|2014|6/20/2014|8 Closed|Yemen,Republic of|
|P117949|2010|2015|2/2/2015|9 Closed|Yemen,Republic of|
|P117949|2010|2015|6/30/2015|10 Closed|Yemen,Republic of|
|P117949|2010|2016|12/24/2015|11 Closed|Yemen,Republic of|
|P117949|2010|2017|7/8/2016|12 Closed|Yemen,Republic of|
|P117949|2010|2020|6/17/2020|13 Closed|Yemen,Republic of|
|P117956|2010|2020|6/28/2020|1 Pipeline|World|
|P117978|2011|2011||0 Closed|Solomon Islands|
|P117978|2011|2012||0 Closed|Solomon Islands|
|P117978|2011|2013||0 Closed|Solomon Islands|
|P117978|2011|2020|6/5/2020|1 Closed|Solomon Islands|
|P117979|2011|2011||0 Closed|Uganda|
|P117979|2011|2012|10/12/2011|1 Closed|Uganda|
|P118018|2012|2012||0 Closed|Cameroon|
|P118018|2012|2013|7/11/2012|1 Closed|Cameroon|
|P118018|2012|2013|1/16/2013|2 Closed|Cameroon|
|P118018|2012|2013|6/27/2013|3 Closed|Cameroon|
|P118018|2012|2014|1/28/2014|4 Closed|Cameroon|
|P118018|2012|2015|7/26/2014|5 Closed|Cameroon|
|P118018|2012|2015|1/30/2015|6 Closed|Cameroon|
|P118018|2012|2016|8/14/2015|7 Closed|Cameroon|
|P118018|2012|2016|3/3/2016|8 Closed|Cameroon|
|P118018|2012|2017|10/20/2016|9 Closed|Cameroon|
|P118018|2012|2017|4/19/2017|10 Closed|Cameroon|
|P118018|2012|2018|4/7/2018|11 Closed|Cameroon|
|P118023|2010|2010||0 Active|Azerbaijan|
|P118023|2010|2011|9/23/2010|1 Active|Azerbaijan|
|P118023|2010|2011|1/31/2011|2 Active|Azerbaijan|
|P118023|2010|2011|5/30/2011|3 Active|Azerbaijan|
|P118023|2010|2012|12/31/2011|4 Active|Azerbaijan|
|P118023|2010|2012|6/17/2012|5 Active|Azerbaijan|
|P118023|2010|2013|12/26/2012|6 Active|Azerbaijan|
that sustains informal risk-sharing arrangements may well be more common in village-based societies than urban areas with more mobile populations.<sup>19</sup> Comparing how our tests for relative deprivation differ between urban and rural areas also offers a clue as to how the importance of relative poverty might change over time, as the economy becomes more urbanized.

In the light of the above observations, we take two approaches to testing. In both cases, our dependent variable is provided by the answers to a ‘satisfaction with life’ ( _SWL_ ) question. (The question does not refer to any specific aspect of ‘satisfaction with life’. We give the precise question used in section 3.2.) This has probably been the most widely used question for assessing overall well-being in psychology and economics.<sup>20</sup> We shall do one test for RD that is similar to the methods used in past research, except that we allow for interaction effects. This method uses a standard objective measure of economic welfare based on consumption, including that of the geographic area in which the respondent lives. However, our data and methods allow us to take a different approach that avoids the need to pre-judge the comparison group and the precise welfare metric. For this purpose, questions were added to the Malawi survey on the respondent’s assessments of the economic welfare of the family’s ‘friends’ and ‘neighbors.’ This has the advantage that it is tailor-made to the perceptions of the respondent. However, as we also discuss below, that advantage comes with the drawback that there may be latent variables that jointly influence both the respondent’s overall satisfaction with life and how she perceives the welfare of friends and neighbors.

While friends and neighbors are obvious groups for both social comparisons and as generators of positive externalities such as through risk-sharing, there may be other groups that matter. Finding that people do not feel RD with respect to their friends and neighbors does not

> 19 For supportive evidence see Ravallion and Dearden (1988) (using data for Java, Indonesia).

> 20 Surveys of the lessons for economics from the “new psychology of happiness” can be found in Frey and Stutzer (2002) and Layard (2005).

13
evil for the individual [...] fraught with social and economic danger to mankind’. As such, signatory states were required to introduce more punitive domestic criminal laws that punished individuals for engagement in all aspects of the illicit drug trade.

Intended as a ‘final’ and definitive document, the 1961 Convention also restructured the international drug control apparatus. The P.C.O.B. and the D.S.B. were merged to create a thirteen-person body of independent experts, the International Narcotics Control Board (I.N.C.B.), which evaluated national statistical information, monitored the import-export control system and authorized narcotic plant cultivation for medical and scientific need. These powers were subsequently extended under a 1972 amendment, which gave the I.N.C.B. responsibility for developing and implementing programs to prevent the cultivation, production, manufacture, trafficking and use of illicit drugs and for advising countries that needed assistance in complying with the Conventions. The amendment also addressed extradition and required that any bilateral agreement automatically include drug-related offences. While the thrust of the 1961 Convention was toward a tightening of criminal sanctions, the 1972 amendment did introduce an important shift toward addressing demand-side issues. Parties to the 1961 Convention were now requested to provide ‘treatment, education, after-care, rehabilitation and social reintegration’ for drug addicts and users.

# _1971 Convention on Psychotropic Substances_

Although the Single Convention was intended as ‘a convention to end all conventions’ (May 1950) the international community met in 1971 in order to respond to the advances in chemistry and synthetic drug manufacture which had led to new mass markets for psychotropic substances such as amphetamines, barbiturates and hallucinogens that were not incorporated into the existing regulatory framework. The resulting _Psychotropic Convention_ introduced a regulatory regime for these drugs modeled on the manufacturing and cultivation control system set out in the 1961 Convention. This included a schedule of four levels of control that were based, like the Single Convention, on a drug’s therapeutic value and abuse potential.

The 1961 and 1971 Conventions were followed through at the domestic level by repressive domestic drug policies. There was a significant enhancement of police powers to stop, search, raid, hold without charge and electronically tap suspected traffickers, dealers and drug users, while the death sentence or mandatory life 23