rafmacalaba/datause-encoder-data huggingface dataset:
The remainder of this paper is organized as follows. Section 2 defines the diversification index and the country categories used as well as stylized facts for T&T and comparison countries. Section 3 tests econometrically the significance of a number of factors thought to influence diversification. The fourth section discusses FDI inflows’ characteristics in T&T, and relevant policies and measures to facilitate economic diversification in the country based on our findings. The last section concludes.

<!-- Start of picture text --> Figure 1.1: GDP Growth rates Figure 1.2: GDP Growth and Oil Price<br>35.0<br>16.0 0.8<br>30.0 14.0<br>25.0 12.0 0.6<br>20.0 10.0 0.4<br>8.0<br>15.0 6.0 0.2<br>10.0<br>4.0 0.0<br>5.0 2.0<br>0.0 0.0 -0.2<br>-5.0 -2.0 -0.4<br>-4.0<br>-10.0<br>-6.0 -0.6<br>Real GDP Growth - Non-Petroleum Sector<br>Real GDP Growth<br>Real GDP Growth - Petroleum Sector<br>Real GDP Growth Petroleum, crude ($/bbl), % change<br>Sources: WEO, Central Bank. Sources: WEO, WB DEC<br><!-- End of picture text -->

# 2. <u>LITERATURE REVIEW AND DEFINITIONS</u>

Diversification has been an ongoing issue of debate for several decades in T&T. After having implemented various reforms to foster the development of new activities and to reduce its dependence on energy, T&T must now identify the remaining constraints its private sector faces (see Annex 1 for an overview of diversification and industrial policy in Trinidad and Tobago since the 1950s). A number of authors have analyzed in depth the structure of the twin-island economy and listed what they consider as major impediments to a reduction of the country’s industry concentration. Artana et al. (2007) have identified the chief constraints to economic diversification in T&T using the Growth Diagnostic Methodology (GDM) developed by Hausmann, Rodrik and Velasco (2005). Based on the analysis of both macro and micro data, the authors found that the most important factors limiting growth opportunities in T&T are deficiency human capital, high macroeconomic volatility, an inadequate development of infrastructure, limited access to foreign markets, rising criminality, lack of innovation, corruption and a burdensome bureaucracy.

Elias et al. (2007) analyzed T&T’s institutions and documented poorer than expected quality-ofgovernance indicators. The authors claim that in the absence of improvements in terms of governance the country might not be able to achieve sustainable high GDP growth rates. To promote the development of a competitive non-energy private sector, Elias et al. recommend the 4
causality. Biases, such as reverse causation, simultaneity and selection, might be driving the results. However, these results give us important first insights into what might be driving the sustainability of PCG funds across countries.

It is also interesting to consider insignificant correlations of loan losses. First, there is no significant variation in default rates between countries at different levels of economic development. Second, the size of the PCG funds is not robustly correlated with loan losses. Also, the governance structure, loan vs. portfolio approach and timing of the payout are not correlated with the loan losses a PCG fund incurs. Finally, in unreported correlations, we also could not find any correlation of loan losses of PCG funds with the degree that funds restrict themselves to specific target groups.

**-** **<u>Table 7: What explains loan losses multivariate regressions</u>**

|LnGDPpercapita|0.00|-0.01|-0.02|-0.02|-0.01|
|---|---|---|---|---|---|
||[0.92]|[0.61]|[0.32]|[0.37]|[0.66]|
|Ln Total Assets|0.00|0.01|0.01|0.01|0.01|
||[0.58]|[0.18]|[0.10]*|[0.09]*|[0.28]|
|Ln Age|0.04|0.04|0.04|0.04|0.03|
||[0.09]*|[0.08]*|[0.06]*|[0.06]*|[0.18]|
|MutualGuarantee|-0.03|-0.02|-0.02|-0.03|-0.03|
||[0.51]|[0.59]|[0.65]|[0.48]|[0.44]|
|NoRisk Management|0.06|0.07|0.07|0.07|0.06|
||[0.10]|[0.09]*|[0.05]*|[0.06]*|[0.10]|
|Loan Basis|0.00|0.01|0.02|0.01|0.04|
||[0.93]|[0.64]|[0.41]|[0.74]|[0.26]|
|DefaultPayout|0.01|0.00|0.01|0.01|0.01|
||[0.58]|[0.96]|[0.50]|[0.61]|[0.59]|
|||||-0.02||
|GovtFunding|-0.03|||||
||[0.30]|||||
|GovtManagement||0.05||||
|||[0.25]||||
|Govt CreditRisk|||0.07|||
||||[0.06]*|||
|GovtRecovery||||0.09||
|||||[0.18]||
|PrivateResponsibility|||||-0.06|
||||||[0.09]*|
|Constant|-0.13|-0.11|-0.08|-0.05|-0.05|
||[0.36]|[0.46]|[0.56]|[0.75]|[0.72]|
|Observations|37|37|37|37|37|
|R-squared|0.27|0.31|0.37|0.36|0.35|

Note: Asterisks *, **, and *** indicate significance at 1%, 5%, and 10%, respectively.

23
<!-- Start of picture text --> 2<br>Pe2<br>«<br>Ps2<br>”<br>28<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index —*— Low clim. index<br><!-- End of picture text --> <!-- Start of picture text --> ° Nv<br>a<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index —*— Low clim. index<br><!-- End of picture text --> <!-- Start of picture text --> 2So<br>28<br>8<br>©43<br>3<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index }—#*— Low lim. index<br><!-- End of picture text --> <!-- Start of picture text --> ”<br>Ps<br>©2<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index —*— Low clim. index<br><!-- End of picture text --> <!-- Start of picture text --> 8<br>8<br>° Nv<br>a<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index —*— Low clim. index<br><!-- End of picture text --> <!-- Start of picture text --> 8<br>8<br>*3<br>~<br>”2<br>1986 1987 1988 1989 1990 1991<br>year<br>—+— High clim. index }—#*— Low lim. index<br><!-- End of picture text -->
impact on open defecation rates in households without toilets at the baseline, and that are the major beneficiaries of the project, might be because such changes take time to materialize, especially considering project delays in the construction of new toilets. Since the midline survey was undertaken right after the completion of the project interventions, some households with brand new toilets might not have gotten accustomed to using them.

In Punjab, both adults and school-going children surveyed at the baseline displayed high levels of awareness of basic hygiene and sanitation issues. Almost all households reported having soap, and a large majority of baseline survey respondents were aware of the reasons for using soap as well as the ill effects of open defecation on communities’ health in general and children’s health in particular. After the completion of the project interventions, we observed large improvements in hygiene knowledge and sanitary practices among both adults and school-going children—and in the control GPs as well. This was mainly due to statewide information and education campaigns undertaken by the India’s central government as well as the Punjab state government through television, radio, and social media to reinforce the messages of the BCC campaign. Our estimation techniques eliminated these time-varying fixed effects to capture the true impact of the project.

Our results indicate that the BCC campaign had a positive and significant impact in raising awareness of the importance of handwashing before eating and after defecation among adults across all treatment arms. The project’s impact appeared to be strongest on households that had access to toilets at the baseline. For households without access to toilets at the baseline, the project’s impact on adults’ awareness of handwashing before eating seemed mostly insignificant, whereas significant improvement in awareness of handwashing after defecation among adults was restricted to GPs receiving regular project interventions and the intensive school awareness campaigns.

The BCC campaign was also very successful in raising awareness of handwashing among school-going children in all treatment arms. Significant improvements in awareness of handwashing before eating were also observed among subgroups of children from households with and without access to toilets at the baseline. Awareness of handwashing after defecation also improved significantly across all treatment arms among households with access to toilets at the baseline. For households without such access, however, a significant improvement was seen only in GPs where intensive school awareness campaigns were conducted.

While the project was mostly successful in raising awareness of the importance handwashing among adults, it had no significant effect on mobilizing more people to use soap, treat their drinking water, or use safe methods for the disposal of child feces. Similarly, the project’s impact in promoting improved hygiene and sanitation practices among subgroups with and without access to toilets was mostly insignificant.

35
**-7-**

||15 Studie|TABLE**1.3**<br>s<br>of Real Output<br>Levels<br>inNanufe|Lcturin.||
|---|---|---|---|---|
|Author|Number of<br>Products<br>Sampled|Size<br>of Sample|Country<br>Coverage|Reference<br>Years|
|Rostas<br>(1948)|108|22 percent<br>of 1937 US employment|UK/USA|1935 to 1939|
|Maddison<br>'1952)|34|15 percent<br>of Canadian,<br>14 per-<br>cent<br>of UK, and 8 percent<br>of US<br>employment<br>in 1935|Canada/'UK/USA|1935|
|Galenson<br>(1955)|23|17 per cent of US indtitrial<br>gross output in 1939|USSR/USA|1936 to 1939|
|Frankel<br>(1957)|50 <sup>(b)</sup>|18 percent of 1947 US employment,<br>16 per cent of UK 1948 employment|UK/USA<br>|1948/7|
|Paige and<br>Bombach (195'J|380|51 percent of UK, and 48 percent<br>of US manufacturing<br>value<br>added|UK/USA|-|
|Mensink<br>(196f-|78|14 percent<br>of UK 1958 employment|Netherlands/UK|1958|
|Kudrov (1969)|224 <sup>(c)</sup>|substantial, but not stated|USSR/USA|1963|
|Czech Statistica<br>Office/INSEE (19|l 113<br>69)|substantial, but not stated|Czechslovakia/<br>France|1962 and<br>1967|
|West (1971)|15 0<sup>(b)</sup>|31 percent (d)<br>of US shipments|Canada/USA|±963|
|Yukizawa<br>(1978)|60|26 percent of Japanese and 24<br>percent of US value added in 1972|Japan/USA<br>|1958/9, 1963<br>1967, 1972|
|Smith, Hitchens<br>&Davies (1982)|<br>4 87 <sup>(cef)</sup><br> <br>(cef)<br>35 0|<sup>66 percent of UK value addede d</sup><br> 64 percent<br>of US value added(<br>31percent<br>of Germanvalue added(<br>and37 percent of UK value added|<sup>UK/USA</sup><br>f5lermany/UK|1968/7<br>1967/8|
|Smith (1985)|386 <sup>(cef)</sup>|<sup>55 percent of UK value added(pe</sup><br>d<br>53 percent of US value added|UK/USA|1977|
|Davies and<br>Caves (1987)|3 98<sup>(cef)</sup>|<sup>60 percent of UK value addeded</sup><br>61 percent of US value addedU|UK/USA|1977|
|Van Ark (1988)|167-197|38 percent of Brazilian value<br>added, and 29 percent of UK<br>value added|Brazil/UK|19;5|
|Maddison<br>and Van Ark<br>(present study)|171-372<br>192-342<br>200-157|33 percent of value added in<br>Brazil, 39 percent in Mexico, 20<br>percent in USA|Brazil/USA<br>Mexico/USA<br>Mexico/Brazil|1975<br>1975<br>1975|
|(a) Galenson inc<br>(b) In the absen|ludes three<br>ce of infor|mining induste'i-s<br>(coal, iron ore<br>mation from the &.ithors,<br>these are|, oil and natura<br>rough estimates|l gas).<br>.|

(c) Information supplied by the authors.

(d) West does not say how big his sample is, but we derived this figure by comparing the industry codes he uses (pp. 59-61) with 1963 information in the General Summary volume of the 1977 Census of Manufactures.

(e) Refers to number of 'matches' instead of number of matched products.

(f) These figures refer only to directly derived PPPs.
To investigate whether the counter-stereotype susceptibility result for H comes from a shift in preferences that lead to reduced effort or, alternatively, a decline in the ability to perform when identity is blatantly primed (as in Shih et al. 2002, discussed in Section 2), in the remainder of this section we decompose performance into two stages: _Stage 1._ The participant learns what it means to solve a maze. The outcome is binary— success or failure. We measure failure by zero output by a participant during the 30 minutes of maze-solving.

_Stage 2_ . The participant applies and improves his skills. The outcome is the number of mazes solved conditional on success in learning how to solve a maze.

# **_5.3 Failure to Learn How to Solve a Maze_**

Here we consider stage 1. Table 4 shows that failure for H occurs more often in the control than in the identity conditions, whereas the reverse is true for L. To fit a logit model, it is necessary to collapse the two identity conditions and also the two incentive conditions.<sup>10</sup> We estimate Failure = α + β·(subject is H) + γ·(session cues identity) (2) + δ ·(subject is H * session cues identity) + μ·Ζ + error, where the benchmark case is L in Caste Not Revealed. We use the logit results, reported in Supporting Table A2, to predict the probability of failure. Figure 7 reports the results, controlling for individual characteristics. The figure shows that revealing caste reduces failure among H from 8% to 2%, and increases failure among L from 1% to 11%. These changes are statistically significant and robust to the addition of controls for household characteristics. These changes are also consistent with the predictions of stereotype susceptibility: when the participants are made more aware of caste, H are less likely, and L are more likely, to completely fail to learn how to solve a maze. These results suggest that the identity conditions do not depress the ability of H to perform a cognitive task. They suggest instead that the decline we find in H output in Revealed Segregated reflects a change in preferences regarding the provision of effort.

> 10 Otherwise the estimates are unbounded, since some cells in Table 4 are empty.

27
information asymmetry between buyers and sellers. We conjecture that this would in turn impact the distribution of product unit values across different woredas in Ethiopia. However, we were not able to obtain unit values from the Ethiopian manufacturing panel data to conduct the price dispersion analysis for a substantial number of products. In future research, we plan to also explore whether household survey data analysis could provide evidence on the variation in price information access across years and districts.

One open question is whether the potential competition, driven by the increased internet access of buyers, which helps them find the best alternative prices at their fingertips, yields Bertrand competition (sellers underprice each other to capture higher market share) or vertical differentiation (sellers upgrade product quality to capture higher market share). For example, Kugler and Verhoogen (2012) provide evidence of the role of quality upgrading for manufacturing competition in Colombia. Our prior is that price competition would be more dominant for relatively homogenous goods (e.g., cement, concrete, flour, bricks, cloth, etc.), and that quality upgrading competition would be more salient for heterogenous goods. Indeed, we use CPI survey data to compare the standard deviations of retail prices for selected commodities based on surveys in 2008 and 2010 for the month of September. We find that the introduction of 3G is associated with the reduction in dispersion in more homogeneous products like cement, mobile phone apparatus, imported rice and some varieties of barley. By contrast, the price dispersions of items such as beer, coffee beans, cotton and wheat have increased. See Table A.1 in the appendix.

Although it is standard in the trade literature to emphasize the Rauch (1999) Index as a measure of horizontal differentiation, its focus on product homogeneity is better interpreted as reflecting differentiation more generally (i.e., both horizontal and vertical). Indeed, homogenous goods are those traded on a commodity exchange or those that have a quoted price in industry trade publications. Interestingly, the degree of price information accessibility is directly related by Rauch with limited scope for product differentiation. Hence, we will also explore the differential impact on homogenous good suppliers, operating in markets mainly with price competition, as opposed to suppliers in differentiated product markets, competing as well through quality upgrading.

28
———. 2012a. ―New Structural Economics: A Framework for Rethinking Development.‖ In _New Structural Economics: A Framework for Rethinking Development_ . Washington DC: World Bank.

———. 2012b. ―India‘s IT industry and industrial policy.‖ _Let’s Talk Development: A blog hosted by the World Bank Chief Economist_ . Submitted on May 25, 2012. Last accessed July 31, 2012 (http://blogs.worldbank.org/developmenttalk/india-s-it-industry-and-industrial-policy).

Lin, J. Y. and H. J. Chang. 2009. ―DPR Debate: Should Industrial Policy in Developing Countries Conform to Comparative Advantage or Defy It?‖ _Development Policy Review,_ 27(5): 483–502.

Lin, J. Y. and C. Monga. 2012a. ―The Growth Report and New Structural Economics.‖ _In New Structural Economics: A Framework for Rethinking Development._ Washington DC: World Bank.

———. 2012b. ―Growth Identification and Facilitation: The Role of the State in the Dynamics of Structural Change.‖ In _New Structural Economics: A Framework for Rethinking Development_ . Washington DC: World Bank.

Lin, J. Y. and J. B. Nugent. 1995. ―Institutions and Economic Development.‖ In J. Behrman and T.N. Srinivasan (eds), _Handbook of Development Economics_ , 3: 2303–2363.

Lipsey, R. E., E. D. Ramstetter, and M. Blomstrom. 2000. "Outward FDI And Apparent Exports And Employment: Japan, The United States, And Sweden." _Global Economy Journal_ , 1(4).

List, F., 1841. [1930]. _Das Nationale System der Politischen Ökonomie_ ( _The National System of Political Economy_ ), _Volume 6: Schriften, Reden, Briefe_ . A. Sommer (ed). Berlin: Reinmar Hobbing.

Maddison, A. 2006. _The World Economy_ . Paris: Organisation for Economic Co-operation and Development.

McMillan, M., A. Ebenstein, Y. Zhao, and C. Zhang. 2011. ―Understanding the Role of China in the ―Decline‖ of US Manufacturing.‖ Mimeo. Washington DC: International Food Policy Research Institute.

Mendes, S. M., E. C. Teixeira, and M. A. Salvato. 2009. ―Investimentos em Infra-Estrutura e Produtividade Total dos Fatores na Agricultura Brasileira: 1985–2004.‖ _Revista Brasileira de Economía_ . 63(2):91–102.

Multilateral Investment Guarantee Agency. 2006. _The Impact of Intel in Costa Rica: Nine Years After the Decision to Invest._ Washington DC: World Bank.

Mokyr, J. 1990. _The Lever of Riches: Technological Creativity and Economic Progress_ . New York: Oxford University Press.

Naik, G. 2006a. ―Bridging the Knowledge Gap in Competitive Agriculture: Grapes in India.‖ In V. Chandra (ed), _Technology, Adaptations, and Exports: How some developing countries got it right_ . Washington DC: World Bank, 49–81.

59
assets such as bank deposits. More than one-fifth of business sector financial assets are in the form of money and time deposits. This highlights the important asset transfor.ation function of the financial sector.

For the household sector over four-fifths of indebtedness is to financial institutions, while almost one-half of financial claims are on financial institutions. Overall, household financial assets are almost two and a half times household financial liabilities. Nevertheless these liabilities themselves are not negligible, being equivalent to almost one-third of GN!P.

The financial institutions are primarily intermediaries, their net financial position coming to little over one per cent of their gross financial assets. Of the identified financial assets held by domestic non-financial sectors, almost two-fhirds are intermediated through the financial institutions.

The principal domestic financial claims of the government sector arise from loans made to the business and corporate sector, its principal domestic borrowings are from financial institutions.

There is a broad correspondence between the instrument structure of the asset holdings (Table 3) and that of the flow figures (Table 2), though this need not always be the case. The remainder of the paper is concerned only with flow iigures.

# 2.3 Data pitfalls

Various practical difficulties mean that the reliability of flow of funds statistics lags behind that of the national income and expenditure accounts. Furthermore, though the methodology for preparing flow of funds accounts in the United Nations (SNA) is a widely accepted standard, it is 12
suggests that the political determinants are deeply rooted in historical factors such as the country's legal origin ( _LO_ ) and the degree of ethnolinguistic fractionalization ( _ELF_ ) and that these historical factors are exogenous to the current economic structure of the country. We use _LO_ and _ELF_ to generate exogenous variations in _Law_ . Of course, these variables are not exhaustive in explaining the current level of institutional development. However, all we need is that they be a source of exogenous variation in _Law_ .

Several studies have used _ELF_ as an important exogenous determinant of institutional quality (Mauro 1995, La Porta et al.). There are a number of reasons why _ELF_ may have a negative effect on _Law_ . Shliefer and Vishny (1993) suggest that more homogenous societies are likely to come closer to joint bribe maximization which is less harmful than non-collusive bribe-setting. Alesina, Baqir and Easterly (1999) argue that disagreements over the nature of preferred public goods (including institutions) lead ethnically diverse societies to demand fewer of those goods. Presence of different ethnolinguistic groups is also significantly associated with worse corruption as bureaucrats may favor members of their own group (Mauro 1995). Such an environment is hardly conducive to institutional development. Furthermore, the adverse effect of ethnic diversity may not be restricted to the development of the legal framework but also affect the ability of the government to implement the laws in an efficient, impartial and reliable manner.<sup>12</sup> Data on _ELF_ used in this paper are taken from La Porta et al. It is a summary measure of five indices which broadly measure the probability that two randomly selected individuals from a given country do not belong to the same ethnolinguistic

> 12 We note that our Law variable is a summary measure of a large number of governance indicators including the efficiency and impartiality with which they are implemented and observed.

13