rafmacalaba/datause-encoder-data huggingface dataset:
Himanshu (2019) documents trends in Indian inequality between the early 1980s and the present. He shows that while rates of poverty decline and economic growth were impressive during this period, particularly post-2000, measured real per-capita consumption inequality rose only modestly, with a Gini coefficient of just around 0.28 in 1993/94, rising to about 0.33 in 2011/12. The largest increase in measured inequality occurred between 1993/94 and 2004/05, rather than in the high-growth 2000s. Himanshu (2019) goes on to note the current debate in India, raised by recent analysis by Chancel and Piketty (2019), concerning the likely understatement of measured inequality in the NSS surveys due to under-representation of, and possible under-reporting by, the top segments of the consumption distribution in the NSS surveys. Chancel and Piketty (2019) employ a variety of adjustment methods to estimate present-day levels of income inequality in India, which compare to those prevailing at the height of the British Raj in the early 20th century. While the precise level of inequality is difficult to ascertain given the data constraints, the evidence suggests that some increase in inequality did occur alongside the growth in incomes and decline in poverty.

It is unlikely that the structure of economic growth in India from the late 1980s to the present took the form whereby all persons enjoyed rising welfare levels without seeing their relative position in the consumption distribution change. As Deng Xiaoping is reported to have noted in relation to the likely impact of the market-oriented reforms he launched in China, ‘some get richer before others’ (see discussion in Himanshu et al. (2018, p. 125)). This observation invites investigation along two fronts. First, to what extent is it the case that different households and population groups in India have participated to differing degrees in the generalized economic growth process? In other words, is there much relative income mobility, and has it increased over time? Second, are there particular distinguishing features of those population groups that have done particularly well, or alternatively that might have been poorly placed to see their fortunes improve? Pursuing such questions requires looking beyond 7
_Table 20_

|Dependent variable: N|eed of fisc|al adjustm|ent based|on Escola|no et al.(|2014)|||
|---|---|---|---|---|---|---|---|---|
|Variables|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Rigid expenditure, CE|0.058***|0.052***|0.061***|0.053***|0.051***|0.053***|0.051***|0.053***|
|(% of GDP)|(0.015)|(0.013)|(0.014)|(0.013)|(0.014)|(0.014)|(0.014)|(0.013)|
|Rigid expenditure, SS|0.031***|0.029***|0.034***|0.029***|0.039***|0.029**|0.015|0.030**|
|(% of GDP)|(0.008)|(0.007)|(0.007)|(0.007)|(0.008)|(0.014)|(0.019)|(0.012)|
|**Economic factors**|||||||||
|GDP growth (t-1)||-2.093***||-1.963***|-1.850***|-1.962***|-1.934***|-1.960***|
|||(0.424)||(0.427)|(0.408)|(0.429)|(0.415)|(0.436)|
|Inflation (t-1)||-0.016||0.021|-0.000|0.021|0.016|0.021|
|||(0.054)||(0.043)|(0.048)|(0.043)|(0.046)|(0.044)|
|U.S. Interest rate||0.002||-0.002|-0.000|-0.002|-0.002|-0.002|
|||(0.010)||(0.012)|(0.012)|(0.012)|(0.012)|(0.012)|
|**Political factors**|||||||||
|Gini|||0.007|0.005|0.004|0.005|0.005|0.005|
||||(0.006)|(0.006)|(0.006)|(0.007)|(0.006)|(0.006)|
|Rule of law|||0.032|0.023|0.014|0.023|-0.029|0.022|
||||(0.027)|(0.031)|(0.029)|(0.031)|(0.046)|(0.032)|
|Margin of Majority|||0.050|0.041|0.057|0.041|0.057|0.060|
||||(0.123)|(0.125)|(0.124)|(0.126)|(0.129)|(0.165)|
|Election's year|||0.020|0.028*|0.030**|0.028*|0.029**|0.028*|
||||(0.015)|(0.015)|(0.014)|(0.015)|(0.014)|(0.015)|
|**Interactions**|||||||||
|EMEs * Rigidity|||||-0.020<br>(0.013)||||
|Gini * Rigidity||||||-0.000<br>(0.000)|||
|Rule of law * Rigidity|||||||0.003<br>(0.003)||
|Majority * Rigidity||||||||-0.002<br>(0.014)|
|Constant|-0.840***|-0.685***|-1.345***|-1.000***|-0.980***|-1.004***|-0.806**|-1.011***|
||(0.199)|(0.175)|(0.308)|(0.283)|(0.280)|(0.337)|(0.324)|(0.292)|
|Observations|1,521|1,500|1,360|1,342|1,342|1,342|1,342|1,342|
|R-squared|0.115|0.172|0.134|0.179|0.184|0.179|0.181|0.179|
|Number of ifscode|84|84|75|75|75|75|75|75|
|CountryFE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Robust standard error|s clustere|d by count|ry in pare|ntheses|||||
|*** p<0.01, ** p<0.05|,* p<0.1||||||||

- 49 -
2 share of global exports fell from 3.1 to under 1.2 percent -- a decline that implies associated export earning losses of about $65 billion annually (1990 exports of sub-Saharan Africa totaled about $38 billion). The objective of this study is to determine the extent to which "external" barriers and policies in OECD countries contributed to this decline. In addition, the study examines the role played by international transportation costs since recent investigations show the nominal equivalents of these charges on developing countries exports are often considerably greater than tariffs, and policy measures often are available for their reduction.

The study proceeds as follows. First, detailed information on the composition and direction of African exports is examined to identify markets and products on which this analyses should focus. An attempt is then made to determine which African countries and products were most heavily affected by pre-Uruguay Round tariffs and how this situation changed as a result of the negotiations. To help assess the restrictive effects of OECD tariffs, comparisons are made between those facing Africa and the successful developing country exporters in East Asia. East Asia is used as a standard for comparison since the tariffs applied to its exports did not stop these countries' sustained export-led industrialization drive after the mid-1960s. Profiles of pre-Uruguay Round nontariff barrier protection against African exports are also analyzed, and empirical analyses are undertaken to show and evaluate the changes resulting from the multilateral trade negotiations. The possibility that some elements of the Uruguay Round agreement on NTBs may have negative effects on African countries export prospects is considered, and policies Africa could adopt to avoid these adverse effects are discussed. In addition, this report also examines a number of policy options relating to tariffs and NTBs the OECD countries might adopt to improve the competitive position of African exports.

Using balance of payments information and national customs statistics the study examines the influence of air and vessel transport costs by estimating their ad valorem incidence on African exports relative to those on similar products from other countries. Given their transit problems, freight cost information for the "land-locked" countries is compared with that for other African exporters in order to determine the magnitude of the adverse differential transport barriers they face. The concept of "effective" protection is employed to assess the influence of transport costs on the location of export oriented industries in Africa, and to determine how freight costs affect African countries' ability to pursue natural resource based industrialization strategies. The study concludes with an overall
(health, education) or public services (defense, internal security). However, such diversion would tend to directly cut government’s contributions to public welfare.

In the case of a renewable energy mandate, a fixed share of total electricity generation should come from renewable energy sources. This implies that the cost of electricity supply ele ren would increase as long as pt < pt .

Unlike in the case of a subsidy, however, this cost difference is borne directly by electricity consumers. Thus, compared to the case of a subsidy where electricity price does not change due to renewable power sources, electricity grids have to increase their price to recoup these costs. If we designate the cost at which the all electricity is supplied in the _n_ ren absence of renewable energy (i.e., baseline case) as _pt_ and the cost of renewable energy as ren pt , the incremental electricity supply costs incurred due to the mandate is estimated from the following relationship: Whenever the government income drops due to policy changes, it raises a tax on fossil fuels in order to keep real government purchases at BAU levels.

# **2.3. Data**

The model is based on three types of data: 1) Moroccan input-output and national accounting data, which are summarized in a SAM; 2) the sectoral energy consumption and CO2 emissions data; and 3) the elasticities of substitution and transformation. The SAM is for year 2007. The sectors and commodities used in the SAM presented in Table 1. In order to discuss policies that promote renewable power generation, the SAM disaggregates the electricity sector into the four power generation technologies hydro, thermal, wind, and solar. CO2 emissions coefficients were calibrated using the fuel combustion data the SAM. Non-combustion emissions are assumed to be proportional to the output levels. Our assumptions about elasticities are based on existing studies by Paltsev et al. (2005) and Timilsina and Shrestha (2007) and are presented in the Appendix and in Figures 3, 4, and 5.

## **3. Renewable Energy Scenarios Simulated**

12
# VII. **Conclusions**

This paper has presented<sup>findingson institutionalfactors that affectthe investment</sup> climate for infrastructure<sup>using recent data fromthe nine largestLatinAmericancountries.We</sup> find that the most significant<sup>determinantof privateinvestmentvolumes overall(after lagged</sup> GDP) is the passage of<sup>legislationliberalizingthe investmentregime.This is important because</sup> it indicates that the legal<sup>basis for reformis probablymore criticalin determiningthe qualityof</sup> the investment climate<sup>thanspecific aspectsof the institutionalframeworkgoveming private</sup> sector participation. We<sup>also find that the generalrelationshipof privateto publicinvestment is</sup> one of substitutability.

The results on regulatory<sup>structureunderline investors'need for stability and</sup> predictability and reflect<sup>the historicalexistence of strong executivebranchesin most Latin</sup> American countries. A<sup>particularly intuitive result isthat privateinvestmentis positively</sup> associated with the independence<sup>and credibilityof the regulator,particularlyitsability to</sup> commit.

Over the period analyzed,<sup>controllingfor other factors,the water sector received</sup> significantly less private<sup>investmentthanother sectors whileprivateinvestmentinpower was</sup> relatively higher than<sup>in the other sectors.The sectoralanalysis indicatesthatthe water sector</sup> differs materially from<sup>the other threesectors: private investment in water is not significantly</sup> affected by the passage of<sup>reformlegislationin the sector and publicexpenditure is very</sup> important and only mildly<sup>substitutablefor private spending.Politicaleconomyconsiderations</sup> appear to make private<sup>investors morewary of enteringthewater sectorthan the roads, power</sup> and telecoms sectors.

23
purchase of a household durable good, or schooling. None said that they saved for medical expenses.

In a moziki, members not only make periodic savings into a pool, but also contribute regularly into an emergency loan fund. The pool financed loans to members in cases of births, deaths, marriages, or hospitalizations. In a survey of 54 moziki members, 10 had received loans in the past year, of which 4 were related to health (births or hospitalizations). Borrowers repaid loans without interest. In two moziki, members facing extreme difficulties could request a special collection from which the proceeds were given, not loaned, to the member in need.

## F. STRENGTHENING EXISTING INSURANCE SYSTEMS

The existing insurance systems, while vibrant and innovative, could benefit from several steps.

## 1. Training

Training in the basic concepts and administrative aspects of health insurance schemes should be offered at the School of Public Health, University of Kinshasa, at successfully functioning systems such as Bwamanda, and through refresher programs offered by FONAIMES, SANRU and the Sante Pour Tous project. A manual about the management of health insurance plans should be developed for this training. The training should consider both general principles (how to calculate premiums based on actuarial data) and an analysis of the experiences of functioning plans in Zaire.

# 2. Exchange Visits

An intra zone program of staff exchanges or site visits should be established. The existing systems could invite personnel from nearby zones to observe their system and adapt their forms and procedures. For example, under the sponsorship of officials for Equateur Region, the health zones around Bwamanda (e.g. Tandala and Gemena) could be given assistance in adapting and replicating the Bwamanda system.

# 3. Information Systems

Without a standardized information system and monitoring procedures, the costs and benefits of a health insurance system are difficult to evaluate and almost impossible to compare with other plans. To help existing insurance systems and possible future efforts, an appropriate coordinating agency (SANRU, PASS, or the Ministry of Health) should develop guidelines for information collection which would assure that utilization and accounting data are adequate for evaluation purposes (for example, availability of utilization and financial data by major payment categories: insured, employed, uninsured and unemployed).

Data analysis was hindered by the fact that none of the plans appeared to have a unique identifying number for each member. With decentralized enrollment through health centers in Bokoro and Bwamanda, each health center tended to develop its own numbering system. A comprehensive system would be easy to develop, in which the first digits represented the health center, the middle digits the village and the family, and the last digits the individual.

# 4. Technical Assistance

Technical assistance can help each plan tailor the lessons learned from the three areas above to their own site, and to implement new accounting systems or policy changes.

61
15 (estimated) inventories and liquid assets, ASS 1. This is consistent with the idea that firms tend to match the maturity structure of assets and liabilities, as implied by the conventional wisdom and as predicted by the more formal model by Hart and More (1994). It is also consistent with the hypothesis that fixed assets may be a better form of collateral for long term debt, so that their availability is associated with longer maturity of debt. Finally the growth of real sales, GYREAL 1, has a positive but not significant effect on maturity.

One important issue that deserves to be investigated is whether changes have occurred over time in the determinants of access to long term credit and, conditional on having access, on the maturity structure of debt. In particular, we would like to know whether financial liberalization has introduced any change in the allocation mechanism of long term debt. We have used the longer SC2 sample to obtain some evidence on this **8** issue. In Table 11 we have reported the results obtained estimating the sample selection model for the SCI sample. After some experimentation, we have allowed the coefficients on lagged operating profits as a proportion of total assets (PROFI) and on the lagged value of the logarithm of real assets (LRTA1) to vary before and after liberalization, both in the access and maturity equation (in Table 12 LD is a dummy variable that equals one from 1989 onward).<sup>9</sup> The results suggest that the probability of having access to long term debt before financial liberalization is positively related to size and leverage and negatively related to profits. These results are similar to those obtained for the SCI 8 In order to investigate the effect of financial liberalization, it would have been desirable to be able to link the two samples in order to cover a longer data period. both pre and post liberalization. As we have already explained this is not possible.

> 9 Although financial liberalization started in 1984. it has been a process and it has included set backs. We have also experimented with different breaking points. obtaining similar results.
and other efforts to remove obstacles facing private business. For example, in Chapter 2 McCaig and Pavcnik note that Vietnam was ranked 99th out of 185 countries in 2013 in the World Bank’s “Doing Business” indicators, “slightly behind China, ranked 91st, and ahead of such countries as Indonesia and Bangladesh.” Yet Ghana ranks 27 countries ahead of Vietnam, in 64th place. According to the indicators, it was considerably easier to get credit in Ghana than in Vietnam, paying taxes was less of a hassle, insolvency was much more quickly resolved, and access to electricity was less problematic. In terms of how well investors are protected, there is a whop- ping 40-point difference between the two countries, in favor of Ghana.

Other cross-national indexes tell a similar story. The Cato Institute’s Index of Economic Freedom, which attempts to quantify the extent to which economies are free of government encumbrance, ranks Vietnam in 96th place, compared with 71st place for Ghana (Gwartney, Lawson, and Hall 2012). (This is for 2010, which is the latest year for which data are available.) A reasonable objection to these comparisons would be that what matters is more the change than the level of an index. Economic progress may be more a function of how much policies have “improved” than where they stand at the end of the relevant period. But here too, it is hard to make the case that Vietnam looks better than Ghana. Both countries have undertaken significant reforms since the 1980s, opening up their economies to trade, reducing the role of the government, and deregulating. Ghana’s summary rating on the Cato Index steadily rose (on a scale from 0 to 10) from 3.05 in 1980, to 5.53 in 1995, to 7.09 in 2010. Unfortunately, Cato does not provide a comparable series for Vietnam over the full period, so a direct comparison is not possible. But in light of the scale of improvement in Ghana’s rating, it is difficult to imagine that Vietnam could have done much better. (To get a relative sense of these ratings, note that the United States had a rating of 7.70 in 2010.) None of this is to deny the possibility that Vietnam’s government does indeed provide a more hospitable environment than Ghana for private business, both by nurturing new economic activities and by removing obstacles that existing ones face. The point is that the way such an environment is constructed is subtler than what is captured by standard indexes and conventional types of policy advice. Although economic liberalization and removal of red tape may foster private investment, the comparison with Ghana suggests it would be a mistake to describe Vietnam’s strategy in those terms—or those terms alone. Of course, a similar argument could be made for many other East Asian success stories as well.

18
14 significant determinant of access. The explanation for both these results may be that the effect of bank association or age is basically subsumed by the size variable, given the high probability that larger firms are group members and, at the same time, older.

The overall past degree of leverage, LEVI, is positively related to access to long term debt. Past access to both short term and long term debt may work here as a predictor of the ability to obtain long term debt (more on the role of leverage below). The initial stock of liquid assets, LASKI, does not play, instead, a statistically significant role.

In Table 10 we report the results for the SC 1 sample from estimating a sample selectiorf model for the length of debt maturity, using standard two steps procedures. The dependent variable is long term debt as a proportion of total debt, including trade debt, MAT. We report the results obtained when either a probit model or a logit model is used in the first step. The coefficient of cash flow in the maturity equation is negative, which emphasizes the worries we have already express concerning criteria for the allocation of long term directed credit in Ecuador. Paralleling the results for the access, the length of maturity is positively and significantly related to lagged leverage. As we have already explained, this latter result may reflect the fact that having obtained debt in the past is an indication of the ability to obtain long term debt in the future. It is also consistent with the idea that higher leverage increases the risk of liquidation and makes long term debt more attractive for firms. The length of maturity is also positively associated with size, but the association is not very significant.

There also evidence of a very strong and positive association between lagged asset maturity (proxied here by the ratio between fixed capital and the sum of fixed capital
third countries. This classification helps in determining the “natural” groupings (i.e. “cluster”) of observations in our data set based on a transparent statistical approach. In order to gauge the contribution of different policy areas in the outcome of the clustering, we characterize each group of agreements in terms of provisions coverage by policy domain. Controlling for the development level of participating countries, and for time periods, we estimate the marginal effect of the 18 policy areas on the probability of an agreement being in one of the two extreme clusters with respect to the medium one.

In a second step we estimate an explicit bilateral trade function taking stock of the clustering of agreements. Here again, we let the data speak and estimate what is the mean impact on trade of belonging to a PTA positioned in a certain cluster. Note that a large part of the literature estimating the impact of PTAs on trade is flawed because it does not control for the right benchmark in terms of trade cost, namely domestic trade. Importantly, we take the gravity equation seriously and embark internal trade flows in our estimation of the trade effects of the different types of PTAs. We compile the largest database for which internal and international trade is available in a panel, based on the last release of UNIDO data.

The last step of the analysis illustrates how to perform counterfactual exercises. We firstly move PTAs of interest away from their cluster towards a more ambitious one (i.e. a PTA cluster associated to higher trade, as estimated in the second step) and examine the effects of such policy reform of preferential agreements in general equilibrium. Since we are not changing the network of trade agreements but only their content, this exercise captures a variation in the intensive margin of PTAs. We then simulate the economic impacts of a policy at the extensive margin, consisting in signing new agreements (with different content and, hence, at different levels of ambition). To provide a quantitative illustration, we concentrate on the Latin America and the Caribbean and the East Asia and Pacific regions, although the approach could be applied to a more general and systematic analysis of prospects for PTAs.

The rest of the paper is structured as follows. Section 1 describes the rich data set used in our exercise and characterizes the clusters of PTAs in terms of commonalities in their content. Section 2 presents the methodology used to measure the ex post impact of the different types of PTAs and characterizes these clusters in terms of their impact on trade. Section 3 shows how to exploit the information on the trade impact of PTAs of different types in a general equilibrium framework for an endowment economy in order to simulate counterfactuals for the world economy, countries in Latin America and the Caribbean,and countries in East Asia and Pacific. Section 4 concludes.

4