rafmacalaba/datause-encoder-data huggingface dataset:
32 price of cotton and coffee as explanatory variables, Frederick's study is most likely misspecified. The studies based on the Nerlove methodology could be misspecified, as some relevant prices are missing. Irrigation, roads, and human capital could well be important in Trail et al. (1987). Population density is most likely important in explaining paddy area in Schalky and Oczkansky (1992).

Simultaneity is an issue in some of the models. In Binswanger et al. (1987) roads, urban wages and population growth are probably endogenous.

Concerning the pooling issue, what was said about Binswanger et al. (1987) in the previous section holds here. Regarding the asymmetric response of price changes, with the exceptions of Olayemi and Oni (1972), Trail et al. (1978) and Jaforullah (1993), all other authors fail to deal with this issue. Olayemi and Oni (1972) indicate that the short-run rising price elasticity is 1.217 and that of falling price is 0.643. The authors formally test the hypothesis of price segmentation and confirm that Nigerian farmers are more responsive to price increase than to price decrease. A shortcoming, however, is that the ex-ante response may deviate from the ex-post one. Trail et al.(1978) obtain the following short-run elasticities: 0.105 for symmetric supply function; 0.90 and 0.068 for increasing price and decreasing price, respectively, in the context of the Wolffram technique; and 0.442 and 0.086 for increasing price and decreasing price, respectively, in the context of the modified Wolffram technique. The latter is the best model. The authors model the case of short-run asymmetry and long-run symmetry by using an Almon lag model. Jaforullah (1993), among others, obtain the following elasticities with the modified Wolffram technique: 0.15, 0.32, 0.20 and 0.41 in the short-run (price falling and rising) and long-run (price falling and rising), respectively. Misspecified reversible function gives rise to an elasticity of 0.12 and 0.28 in the short-run and long-run, respectively.

The results from asymmetric area responses are important in the debate concerning the potential deleterious environmental effect of price increases and price decreases.
an additional 1.19 days in _every 2-week paycycle_ .<sup>29</sup> In addition, these effects are not simply reflecting a substitution away from other income-generating activities outside of the factory jobs: we find no treatment effects on earnings outside the factory. This is consistent with the fact that, at baseline, 89% of workers report having no earnings outside of their factory job, and on average, 93% of total income comes from factory earnings. Consequently, these treatment effects reflect an increase in total earned income.

In Cols. (4)-(5), we verify that our Phase 2 treatment effects are not driven by Phase 1 treatment status. Specifically, since we cross-randomize treatment assignment across the two Phases, one potential concern is that treatment effects may be influenced by workers who were assigned to Private accounts in Phase 1 and then lost access to these accounts in Phase 2. In Col. (4), we exclude from the analysis workers who were assigned to Private accounts in Phase 1, so that the sample includes only workers who were in the Control group in Phase 1 or workers who were not in the Phase 1 sample at all. The results are nearly identical: among such workers, the Private treatment increases output by 214 FCFA or 12.8% ( _p_ =0.034). Moreover, even if we exclude all workers in the Phase 1 sample, and only examine effects on the 120 workers who only joined the study in Phase 2, the treatment effects are similar and remain significant (Col. 5, _p_ =0.020). Moreover, we cannot reject that the treatment effects estimates across Cols. (3), (4), and (5) are the same ( _p_ =0.427); in other words, the effects across these three samples are statistically indistinguishable. In addition, we verify that our treatment effects are robust to alternate empirical specifications, including using only intervention period data to examine treatment effects (Appendix Tables A3 and A4).

These results indicate that reducing the likelihood of transfer requests on savings has a marked impact on workers’ willingness to supply labor. This, in turn, has a large impact on their total earned income.

# **7.3 Heterogeneity in treatment effects**

Consistent with our hypothesized mechanism, the Private accounts have larger labor supply impacts among workers who report more redistributive pressure at baseline. In Table 4, Col. (1), we examine heterogeneity by whether workers state that they cannot accumulate savings due to redistributive pressure—i.e. those that agree or strongly agree with the statement, “I have difficulty saving over time for large goals, because if I put money aside, someone else will need it for something urgent”. Among such workers, being offered the option to shield savings from transfer requests increases earnings by 249 FCFA or 15.0% ( _p_ =0.018).

> 29The average treatment effect on daily earnings is 184.4 FCFA, corresponding to a 2,213 FCFA increase per paycycle (comprised of 12 workdays). Mean daily earnings conditional on working among the Non-private group is 2,626. This gives 2626/2213 = 1.19 workdays per paycycle.

27
comparing the effect of port efficiency on imports versus exports, they find that the coefficient is higher for exporter than importer, which implies that global trade flows get a bigger boost when the exporter's port efficiency improve. For landlocked countries, Wilson, Mann and Otsuki (2003a) show that the ports are as important for both import and export as in non-landlocked countries. For island countries, it appears that ports are more important for their import and less important for their export compared to non-island countries. Similar result was found by Limao and Venables (2001).

Wilson et al. (2003a, 2003b, 2004) show that the customs environment has a significantly positive effect on trade of the importing country. Moreover, they argue that trade facilitation is a possible avenue for reducing the cost of imports through customs improvements. OECD (2007) uses a metrics of customs and administrative procedure from the World Bank "Doing Business" survey (2005) to estimate a gravity model. The study concludes that all countries can benefit from more efficient customs and administrative procedures, with the greatest benefits accruing to those reforming countries with the least efficient customs and administrative procedures.

Wilson et al (2003a, 2003b, 2004) find that improving the regulatory environment of the importer and exporter has a positive and significant association with trade. De Groot et al. (2003) also show that a better quality of formal institutions tend to increase trade. Rodrik et al (2002) conclude that the quality of institutions has a significant and positive effect on country's total trade flows. Otsuki et al. (2001) find that African export of cereals, nuts and dried fruits will decline by 4.3 (cereals) and 11 (nuts and dried fruits) percents with a 10 percent tighter European Union standard on aflatoxin contamination levels of these products. Francois and Manchin (2007) also find that exports performance depend on institutional quality.

Wilson et al (2003a, 2003b, 2004) use the percentage of companies that use the internet for e- commerce to assess the effect of internet. They conclude that E-business usage has a positive and significant effect on trade. Freund and Weinhold (2004) show that an increase by 10 percent in the relative number of web hosts could increase by one percent the country’s trade flow. Choi (2003) shows that when the number of the internet hosts or users in a host country increased by 10 percent, the foreign direct investment inflows increased by more than 2 percent. Fink et al. (2005) suggest that a 10 percent decrease in the bilateral calling price is
- 6 -

**Table 5:  Second Pillar Assets in Hungary and Other Reforming Countries (% of GDP)**

|**Country**|**First Year of Operation**|**At 7**<sup>**th**</sup>**Year**|**2004**|
|---|---|---|---|
|Hungary|1998|4.0|4.0|
|Argentina|1994|7.1|12.0|
|Bolivia|1997|20.9|20.5|
|Chile|1981|13.5|59.1|
|Colombia|1994|-|10.3|
|Costa Rica|2001|-|2.7|
|El Salvador|1998|13.7|13.7|
|Mexico|1997|5.7|5.8|
|Peru|1993|4.1|11.0|
|Poland|1999|-|8.0|
|Uruguay|1996|9.3|16.1|

Source: HFSA, AIOS 18. As shown in Table 6, the slow growth of the ratio of pension assets to GDP in Hungary has been primarily due to the slow initial growth of contributions and the poor return performance in the first years of implementation. The flow of contributions remained basically stagnant in 2000 – 2002, and only started accelerating in 2003 and 2004, especially the latter year. The contribution of asset returns should also have increased during the whole period of implementation, in line with the increase in assets, but also remained small and stagnant during most of the period due to low rates of return in most years, as examined in more detail in Section IV. Operating fees did not subtract too much value from assets but have been increasing steadily. This is a trend that is cause for concern, as noted in Section V.

**Table 6: Sources of Growth of Pension Assets over GDP, 1998 – 2004**

||**1998**|**1999**|**2000**|**2001**|**2002**|**2003**|**2004**|
|---|---|---|---|---|---|---|---|
|Assets (% of GDP)|0.29|0.79|1.33|1.91|2.47|3.02|3.97|
|Change (% of GDP)|-|0.50|0.54|0.57|0.56|0.56|0.95|
|Sources (% of GDP):|-|0.47|0.52|0.53|0.51|0.63|0.94|
|Contributions|0.27|0.49|0.61|0.66|0.68|0.87|1.06|
|Asset returns|-|0.08|0.11|0.12|0.16|0.12|0.27|
|Fees and charges|-|-0.03|-0.04|-0.06|-0.07|-0.08|-0.10|
|GDPgrowth|-|-0.06|-0.15|-0.19|-0.26|-0.28|-0.30|

Source: Appendix A.

19. The slow growth of contributions to the second pillar was due to several factors, including the failure to increase the contribution rate according to the original plans, the stagnation of second pillar membership in 2000 – 2002, the decrease in the contribution ceiling relative to the average covered wage, and the relatively low covered wage bill in Hungary. As shown in Table 7, the contribution rate was maintained at 6 percent until 2001, and only increased with the return of the socialist government in 2002. The base of the contribution to the second pillar stagnated at about 10 – 11 percent of GDP in the same period, reflecting not only the stagnant membership in 2000 – 2002, but also the failure to increase the contribution ceiling in line with the increase in the covered wage. Finally, the
information about customers or arbitration services extended 4 percent more of their goods on trade credit.

Unlike the Johnson and Woodruff (1999) results for Vietnam, JMW (2002) finds evidence that the court systems in the five transition economies did sustain additional trade credit. Specifically, suppliers who said that courts were effective extended 5 percent more of their products on trade credit. However, this significant increase held only for relationships with new customers, not those with which the supplier already had a relationship. Moreover, JMW found that customers who had greater faith in courts expressed greater willingness to switch suppliers, even when the supplier was its only current one or when goods were customized to the customer. Their evidence indicates that functioning courts are crucial because they enable trade between partners who are unfamiliar with one another, and thus expand arms-length contracting in an economy.

# **_China_**

As described above, trade credit in China in the late 1990s and early 2000s operated on two tracks: along one track, profitable private firms extended trade credit to their customers who lacked access to external funding, which could be viewed as supportive of the equity stake view of trade credit; along the other track, state-owned enterprises, which enjoyed favored access to credit from the state-dominated banking system regardless of their profitability, extended credit to prop up their failing customers, which had piled up arrears, in line with the redistribution view (though this was not redistribution that supported productivity and growth). The disciplining effect of partial privatization of some Chinese SOEs was intended to improve their financing decisions and operating performance, though Huyghebaert et al. (2014) still found that publicly listed SOEs that issued new shares and borrowed more from banks had significantly higher levels of accounts receivable than others, which they interpreted as evidence that these SOEs used better access to external funding to ease the financial constraints of their trading partners. It seems likely that a large share of this trade credit was still used to prop up struggling customers.

Not surprisingly, the drivers of these two types of trade credit were very different. For example, Fabbri and Klapper (2016) provides evidence from the ‘private firms’ track indicating that suppliers with weak bargaining power over their customers extended more trade credit and 20
17 industrialized Baltics and the more resource-intensive other republics of the FSU. Whether the complementarity will hold in the future remains to be seen. Past trade patterns are unlikely to reflect true comparative advantages of the former centrally planned economies. Existing factor endowments imply limited complementarity in the future. Similarity of skill levels between the Baltics and the larger FSU countries suggest some similarities (figure 2). On the other hand, the larger endowments of resources in general in tde other FSU can lead to different specializations between them and the Baltics in the future.

Beyond trade in goods the Baltics had important links with other FSU republics in the services sector. Their geographic location is likely to maintain some complementarities vis-a-vis other FSU countries in the future. A union without border controls could make maintenance or development of these links easier. Much of the trade between the FSU and the West transitted through the Baltic ports with rail and road links to the Russian mainland. As Russian trade with the West expands its own port capacity is unlikely to suffice in the short run. This offers substantial potential for the Baltics as transit centers. The Baltics also have potential as a transit corridor for land transportation between the large St. Petersburg economic area, Finland and the rest of Europe. But these benefits are not sufficient to justify a union and can be resolved by simplifying border and other formalities.

# iii) Level of barriers

Trade creation and diversion are influenced by the level of pre-existing trade barriers as well as barffers between the members in the regional trading arrangement. The level of emerging external protection among the Baltics and the rest of FSU is quite different. In Russia the average level of duties has been around 18% for preferential partners and the double for nonpreferential ones. Export taxes and other trade restrictions are numerous (World Bank 1993). Recent problems with reform in Russia also suggest a more protectionist tr in policies. The Baltics have relatively moderate levels of protectionl'.

**IC** Unweighted average duties in Latvia were 10% for **MFN** trade and 13 % for non-MFN trade (without specific duties), although dispersion of rates was high (range 0-35%). In Lithuania average duties were only 3%, although duties on many locally produced products were 10-25 % with zero rates on inputs. Both countries maintain some export restrictions, some NTBs. Estonia has zero duties on nearly all goods.
_cronyism_ , whether or not they involve monetary kickbacks, may also be included in a broad definition of corruption.

For our purposes, and to demarcate the field of investigation, corruption is defined as a “bribe tax”, a certain amount of money necessary to enforce a contract between an individual and the state. In this asymmetrical relationship, the state – or its agents - define the property rights of individuals and enforce them with a monopoly on the legitimate use of force. The institutions that govern this type of “vertical” transactions between the state and its citizens are defined by Acemoglu and Johnson (2005) as property rights institutions and are distinguished from contracting institutions that regulate “horizontal” transactions among ordinary citizens. Property rights institutions are inefficient when they allow those who control the state to extract rents from producers (Acemoglu, 2006) and the extortion of bribes from firms may be viewed as a form of rent extraction perpetrated by bureaucrats (Shleifer and Vishny, 1998).

Another important task is to identify a suitable data source to quantify the extent of corruption. A first type of data is based on _expert assessments_ , such as the International Country Risk Guide. A second type takes the form of a _meta-database_ , assembling the results of a number of perceptionbased surveys. Popular indicators in this group include the Corruption Perception Index (CPI) estimated by Transparency International or the indicator for Control of Corruption included in the World Bank’s World Governance Indicators. All these assessments present a high degree of correlation, indicating that they concur in identifying levels of corruption across countries and are, therefore, virtually interchangeable for the purpose of cross-country econometric analysis. A third source of measurement of corruption is provided by _enterprise surveys_ , which have the benefit of allowing to link the occurrence and effects of corruption to a number of firm-level and country characteristics.

Our analysis intends to exploit the advantages of the latter type of data by using the information contained in the 2009 Business Environment and Enterprise Performance Survey (BEEPS) of over 11,000 firms in 28 countries of Central and Eastern Europe and Central Asia. The sample of countries is very diverse. It covers all the formerly communist countries of Europe and the Former Soviet Union, which have undergone the profound institutional transformation connected 3
among different policy alternatives that are compatible to a given public expenditure; instead, it focuses on the total fiscal cost. Furthermore, OIA (as well as BIA) says little about the extent to which a certain program or policy influences the behavior of beneficiaries (or nonbeneficiaries). Nonetheless, the exercise can be useful from a policy point of view to the extent that it relates to both demand and supply factors, such as individual characteristics and public spending, respectively.

# **3. Opportunity Incidence Analysis in Practice**

# **3.1 Relevant opportunities and circumstances**

From a conceptual viewpoint, HOI analysis typically focuses on a number of basic services that are critical early in life to provide the opportunities to allow a child to grow up in a reasonably healthy environment, receive education, and access affordable health services to function productively in any given society. In practice, in selecting the final set of indicators among the list of basic opportunities that can be analyzed as “opportunities” for a given country, two issues are of paramount importance. First, indicators must be available from existing data sources. For example, in one of the case studies analyzed in this paper, Côte d’Ivoire, a series of household surveys have been administered since 1985. The surveys are nationally representative and fairly comparable over time. In addition to the long time period covered, analysts can take advantage of the information on household income and spending, which are usually not available in other surveys used for the HOI study of African countries. In contrast, in the case of Liberia, there is only a Core Welfare Indicator Questionnaire (CWIQ), which provides information aggregated at the national level from which to build the analysis. Second, the indicators chosen must be relevant for the specific country and provide useful information. In terms of relevance, the broad categories of basic opportunities identified in earlier work (education and access to housing services) correlate to capabilities that are almost universally accepted as necessary for a productive life. However, in defining the precise indicators within each broad category, country-specific factors need to be taken into account. In particular, it is important to note that an HOI is useful, in terms of adding value to what is already known, if the coverage or incidence of a particular opportunity is reasonable in a country. If, for example, only a small share of the population has access to a given opportunity, the HOI analysis will not provide much new information because almost everyone remains equally excluded from the basic service. Conversely, if the coverage of a given public service is almost universal, the HOI analysis will not provide much value added because everyone is almost equally included in the service.

Table 1 lists the set of opportunities and circumstances constructed with the data used for this study and for the six sample countries: Côte d’Ivoire, Liberia, Paraguay, Tajikistan, Thailand, and 9
Poverty and Social Policy Division Technical Department Africa Region The World Bank Correcting for Sampling Bias in the Measurement of Welfare and Poverty: The Case of the Cote d'Ivoire Living Standards Survey

**Lionel Demery Christiaan Grootaert**

This paper is an output of the research project "Poverty and the Social Dimensions of - Structural Adjustment in CBte d'Ivoire, 1985-88 A Policy-Oriented Analysis" (RPO 67526). The authors would like to thank Gi-Taik Oh and Meera Venkataraman for excellent computer programming and general analytic assistance, and Audrey Cox and Li Ting Fong who processed the paper.
observe migrants. The income regression is estimated using data for period T . Migrants are de fi ned as those who migrated between T and T + t. This implies that migration decision are assumed to be taken based on income di ff erentials at time T , that is, prior to the time at which migrants choose their destination.<sup>8</sup> This appears to be a reasonable assumption given that most migrants in our dataset come from rural areas of Nepal and are unlikely to be particularly good at forecasting di ff erential income trends in multiple locations.

We also examine whether migrants consider relative incomes — rather than absolute incomes — when deciding where to migrate. This point was already touched upon by Stark and Taylor (1991) who showed that households’ relative deprivation in their village reference group is signi fi cant in explaining migration to destinations where a reference group substitution is unlikely and the returns to migration are high. More recent work in economics and psychology has shown that subjective well-being depends on relative achievement, of which one dimension is income (see Fafchamps and Shilpi, 2008 and 2009 for brief surveys of the literature). This raises the question of whether people choose the migration destination that, on the basis of their individual characteristics, promises them a high income relative to that of others in that location. To this e ff ect, we replace yi<sup>hwithy</sup> i<sup>h/</sup> <u>yi</u> in equation (1) and proceed as outlined above. If migration decisions are based on relative rather than absolute income, then the coe ffi cients of<sup>�</sup> δ s −<sup>�</sup> δ i and � � ( η s − η i) z<sup>h</sup> should be positive and signi fi cant only when they are computed using yi<sup>h/</sup> <u>yi.</u> In addition to relative and absolute income di ff erences, the analysis also examines the respective roles of various location characteristics such as housing and food prices, availability of public services, and density of human settlement.

> 8 An alternative strategy for the estimation of pre-migration income distribution in cross-section data is suggested by Bayer, Khan and Timmins (2008).

11