rafmacalaba/datause-encoder-data huggingface dataset:
4

# **II.   HOW IS DIVERSIFICATION MEASURED?**

Measures of economic diversification need to look beyond trade, to capture domestic sector diversification and the underlying dynamic process of structural transformation. _Trade diversification_ and _domestic diversification_ are in principle interlinked, the former reflecting diversification in the external sector, and the latter capturing diversification in the domestic production process across sectors. An underlying theme of this paper is that focusing on the entire structure of production paints a more comprehensive and illuminating picture. Therefore, the two dimensions of diversification are evaluated simultaneously, filling a gap in the existing literature, which has treated them independently. In addition, the analysis focuses on “diversification spurts,” that is, rapid, sustained, significant spells of diversification.

Trade diversification can be achieved along several dimensions. First, diversification may occur across either products or trading partners. Second, product diversification may occur through the introduction of new product lines (the _extensive_ margin), or a more balanced mix of existing exports ( _intensive_ margin). Finally, product-quality upgrading represents a slightly different notion and is evidenced by higher prices for existing exports. Our main data source for trade is an updated version of the UN–NBER data set, which harmonizes UN COMTRADE bilateral trade flow data at the 4-digit SITC (Rev. 1) level.<sup>3</sup> However, while the existing literature typically focuses on the post-1988 period, this paper uses data extending back to 1962. The extended time dimension turns out to be greatly helpful in examining relationships more comprehensively.

Analysis of domestic diversification in frontier economies required construction of a new data set. This paper examines diversification in sectoral output and the sectoral allocation of labor using data from existing and new sources. Existing data sets include measures of value added for 28 manufacturing sectors, during 1985–2010 (from UNIDO, 2011; 3-digit ISIC classification); and labor employment shares in nine economy-wide sectors, during 1969–2008

> 3 The dataset combines importer- and exporter-reported data from COMTRADE to maximize comprehensiveness, while ensuring internal consistency, using the methodology of Asmundson (forthcoming).
# **References**

Abramovitz, M.A. (1986), Catching Up, Forging Ahead and Falling Behind, _Journal of Economic History,_ vol. 46 pp385-406 27, p.p. 197-204 Amable, B. , B. Verspagen (1995) The Role of Technology in Market Shares Dynamics, _Applied Economics,_ vol 27, pp 197-204 Amendola, G., P. Guerrieri, P.C. Padoan, (1992) International Patterns of Technological Accumulation and Trade, _Journal of International and Comparative Economics, vol._ 1, p.p. 211-234 Anderson K, R. Blackhurst (eds.) (1993) _Regional Integration and the Global Trading System,_ New York, Harvester Wheatsheaf Archibugi D. , M. Pianta (1992) _The Technological Specialization of Advanced Countries,_ Dordrecht, Kluwer Archibugi D. , M. Pianta (1994) Aggregate Convergence and Sectoral Specialization in Innovation, _Journal of Evolutionary Economics,_ 4, 17-33 Baldwin R., E. Seghezza (1996) _Growth and European Integration: Towards an Empirical Assessment,_ CEPR d.p. 1393 Bayoumi T., D. Coe, E. Helpman (1996) _R&D Spillovers and Global Growth_ NBER w.p 5628 Bell, M. , K. Pavitt (1995) The Development of Technological Capabilities, in I. ul Haque et al. _Trade, Technology and International Competitiveness,_ Washington, Economic Development Institute of The World Bank Ben-David, D., M. Loewy, (1995) _Free Trade and Long-Run Growth,_ CEPR working paper 1183 Ben-David D., A.K.M. Atiqur Rahman (1996), _Technological Convergence and International Trade,_ CEPR d.p. 1359 Breschi S., F. Malerba (1996) Sectoral Innovation Systems, in C. Edquist (ed.) _Systems of Innovation: Theory and Evidence,_ Oxford, Oxford University Press Caballero R. , R. Lyons (1992) External Effects and Europe's Integration, in L.A. Winters, A. Venables (eds.) _European Integration in Trade and Industry,_ Cambridge, Cambridge University Press Cantwell J. (1989) _Technological Accumulation and Multinational Corporations,_ Oxford, Basil Blackwell 16
# Figure 5: Transmission to the Rest of the OECD of Permanent U.S. Deficit Reduction

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# **Table 8**

Impact of new road on consumption, earnings and assets _Panel A. Consumption and earnings_

||Consumption per|Poverty rate|Night lights|Share of HH|
|---|---|---|---|---|
||capita (log)||(log)|earning _≥_INR 5k|
|New road|0.023|-0.014|-0.003|0.005|
||(0.041)|(0.042)|(0.166)|(0.032)|
|Control group mean|9.551|0.301|1.445|0.148|
|N|11474|11474|11135|11474|
|R2|0.41|0.30|0.66|0.25|

_Panel B. Asset ownership_

||Asset index|Solid house|Refrigerator|Vehicle|Phone|
|---|---|---|---|---|---|
|New road|0.144|0.042|0.009|0.003|0.041|
||(0.134)|(0.029)|(0.013)|(0.024)|(0.042)|
|Control group mean|-0.017|0.220|0.036|0.140|0.444|
|N|11464|11474|11474|11474|11474|
|R2|0.52|0.67|0.27|0.38|0.48|

_<u>∗ ∗∗ ∗∗∗</u> p <_ 0 _._ 10 _, p <_ 0 _._ 05 _, p <_ 0 _._ 01 Notes: This table presents regression discontinuity estimates from the main estimating equation of the effect of new road construction on various measures of welfare. Panel A examines the impact on measures of consumption and earnings. We use imputed log consumption per capita (outcome for Column 1, see Data Appendix for details of variable construction) and share of the population below the poverty line (Column 2). The dependent variable for Column 3 is the log of mean total night light luminosity in 2011-13, with an extra control for log light at baseline in 2001. The dependent variable for Column 4 is the share of households whose highest earning member earns more than INR 5000 per month. Panel B examines the impact on asset ownership as measured in the 2012 SECC. The dependent variable for Column 1 is the village-level average of the primary component of indicator variables for all household assets measured in the SECC. The remaining four columns present estimates for the impact on the share of households in the village that own each of these assets. The specification includes baseline village-level controls for amenities and economic indicators, as well as district-cutoff fixed effects (see Section V for details). Heteroskedasticity robust standard errors are reported below point estimates for all estimates except for consumption and poverty, which report bootstrapped standard errors as described in the data appendix.

38
Vincent 2009; Laso-Bayas et al. 2011; Naylor and Drew 1998; Nfotabong Atheull et al. 2009; Rönnbäck, et al. 2007; UNEP 2014a; Walters et al. 2008; Walton et al. 2006). However, there is also evidence that coastal people hold important cultural values associated with mangroves. A contingent valuation study of mangrove-dependent coastal communities in Micronesia demonstrated that the communities “place some value on the existence and ecosystem functions of mangroves over and above the value of mangroves’ marketable products” (Naylor and Drew 1998, p. 488).

In addition to supporting near-shore fisheries harvested by poor coastal communities, coral reefs also provide valuable shoreline protection against storms. For example, Cesar (2000) estimates the losses, in net present value per square kilometer (km<sup>2</sup> ), in terms of support for nearshore artisanal fisheries and coastal protection from the destruction of coral reefs in Indonesia. The main threats to coral reefs are from poison fishing, blast fishing, coral mining, sedimentation from logging onshore and overfishing. Together, these threats account for present value losses in coastal fisheries of around $0.41 million per km<sup>2</sup> of coral reef destroyed, and present value losses in coastal protection of $0.011 to $0.453 million per km<sup>2</sup> of coral reef destroyed. Evidence from Kenya indicates that coral reefs may also be critical to larval dispersal to fishing areas, which could affect the effectiveness of marine reserves and closed fishing grounds in inducing stock recovery and thus eventual re-opening to fishing (Rodwell et al. 2003). Coral reefs also have important cultural and non-use value to neighboring coastal communities; many cultural and religious traditions have evolved in tropical coastal zones that honor the dependence of local communities on adjacent reefs and reflect the “bequest value” of preserving this way of life into the future (Moberg and Folke 1999). Studies from other regions show that these coral reef fishery, protection and cultural benefits are significant for many poor coastal rural communities (Badjeck et al. 2012; Barbier et al. 2011; Campbell et al. 2006; Moberg and Folke 1999; van Zanten et al. 2014; White et al. 2000; Zeller et al. 2007).

# **6. Conclusion**

Recent studies indicate that a handful of developing countries contain most of the urban low-elevation coastal zone (LECZ) populations at high risk from the hazards of climate change; for example, 10 cities in developing countries will account for 67% of the future coastal population exposure to the risks from sea-level rise and storm surge (Brecht et al. 2012). This study finds that the global distribution of rural LECZ poverty is also concentrated; in 2000, just 15 developing countries contained more than 90% of the world’s LECZ rural poor.

In addition, rural LECZ poverty is distinguishable by income level. Low-income countries have the highest incidence of poverty among their LECZ rural populations, which declines somewhat for lower-middle-income countries, and then is much lower for uppermiddle-income economies. South Asia, East Asia and the Pacific and Sub-Saharan Africa 32
- BLS. (2011) Counting Green Jobs: Developing the Green Technologies and Practices (GTP) Survey. Conference paper: Stang, S. and Jones, C. Section on Survey Research Methods : JSM 2011

- ____. (2012a) Occupational employment and wages in green goods and services: November 2011. U.S. Bureau of Labor Statistics. News release: September 28, 2012

- ____. (2012b) Green technologies and practices: August 2011. U.S. Bureau of Labor Statistics. News release: June 29, 2012.

- ____. (2013a) Green Goods and Services survey: results and collection. U.S. Bureau of Labor Statistics. Monthly Labor Review. September 2013.

- ____. (2013b) The Green Goods and Services Occupational survey: initial results. Warren, Zack. U.S. Bureau of Labor Statistics. Monthly Labor Review. January 2013.

- ____. (n.d.). Measuring green jobs. U.S. Bureau of Labor Statistics (BLS). https://www.bls.gov/green/#definition (accessed on 06/03/2022)

- Bontadini, F.; Vona, F. (2021) Anatomy of Green Specialization: Evidence from EU Production Data, 1995-2015. Sciences Po OFCE Working Paper, n° 21/2020

- Bowen, A.; Kuralbayeva, K.; and Tipoe, E.L. (2018) Characterizing green employment: The impacts of ‘greening’ on workforce composition. Energy Economics, 72: 263-275.

- BPS (2014). Klasifikasi Baku Jabatan Indonesia (KBJI) 2014. Kementerian Ketenagakerjaan dan Badan Pusat Statistik.

- Consoli, D.; Marin, G.; Marzucchi, A.; Vona F. (2016): Do green jobs differ from nongreen jobs in terms of skills and human capital? In: Research Policy, 45(5), 1046- 1060.

- Dierdorff, E.; Norton, J.; Drewes, D. W.; Kroustalis, C.; Rivkin, D.; and Lewis, P. (2009) Greening of the World of Work: Implications for O*NET® -SOC and New and Emerging Occupations. The National Center for O*NET Development.

- Dierdorff, E.; Norton, J.; Gregory, C.; Rivkin, D.; and Lewis, P. (2011) Greening of the World of Work: Revisiting Occupational Consequences. The National Center for O*NET Development.

- Elliott, R.; Kuai, W.; Maddison, D.; Ozgen, C. (2021) Eco-Innovation and Employment: A Task-Based Analysis. IZA Discussion Papers No. 14028

Eurostat (2009). The environmental goods and services sector. doi 10.2785/31117

- Granata, J.; Posadas, J.; Testaverde, M. (2021) Indonesia’s Online Vacancy Outlook: from online job postings to labor market intelligence 2020. World Bank.

- Granata, J.; Moroz, H. (2022) Identifying Skills Needs in Vietnam: The Survey of Detailed Skills. World Bank.

- Gregg, C.; Strietska-Ilina, O.; Büdke, C. (2015) Anticipating skill needs for green jobs: a practical guide. Skills and Employability Branch Employment Policy Department. ILO. Geneva.

35
- 26 -

- Network externalities may create either excess inertia (too little investment while everybody waits for others to invest in the expansion of the network, which becomes more valuable the more it connects users to others) or excess momentum (too much investment as firms try to establish a first-mover advantage) (Tirole 1988, Economides 1994, Katz and Shapiro 1994)

**The basic tradeoffs.** Altogether the arguments for erecting policy barriers for entry into natural monopolies point to excessive costs of service delivery under free entry regimes or undersupply. To evaluate such arguments ex-ante one would need to have a view on the magnitude of such costs and compare them to the likely losses of efficiency resulting from restraints on competition. Such a tradeoff is by definition impossible to quantify ex ante, but the following general considerations may hold.

- **Costs of establishing networks.** Competition between networks may be desirable if the sunk costs of establishing those networks are "small" relative to the cost of the ultimate service, e.g. lines in telecommunication networks.

- **Government capability.** In cases where government capacity to benevolently and efficiently recognize natural monopoly and establish barriers to entry is weak it is more likely that entry should not be limited by policy (award of monopoly franchises or exclusivity periods etc.). Likewise when monopoly firms are either owned or regulated by a "weak" state the case for allowing competition is strengthened.

**T echnical change.** When technical change is rapid it will be more difficult to circumscribe the domain of natural monopoly and the dynamic benefits of competition will be large.

> - **~Complexity of networks.** As argued above in the discussion of scheduling there is likely to be more value in competing networks the more complex the network is. e.g. logistics networks. This is simply a case where the costs and benefits of maintaining a monopoly are little known and where competition is most needed to find innovative solutions.

# **4.3 The Political Economy of Natural Monopoly**

**Unavoidable political decisions.** Most of these arguments are difficult to translate into practical measures that allow governments to assess the likelihood of wasteful duplication. It is harder still to assess the magnitude of dynamic benefits that need to be weighed against the costs of duplication. The easiest may still be cost function studies as suggested by the contestability literature. But this says nothing about how to factor in dynamic benefits from competition. Arguments about network externalities and games among a small number of players can go both - ways -in favor or against entry barriers depending how the games are specified. The foregoing arguments thus mainly characterize the logic of some arguments. At the end of the daypolitically established biases will be the decisive factor. Good policy should ideally take such
17 Figure 9: Spillovers from U.S. interest rate shocks to EMDEs

- (A) Impact of rising U.S. long-term yields on EMDE equity prices

<!-- Start of picture text --> Percent Monetary Real<br>5<br>4<br>3<br>2<br>1<br>0<br>-1<br>-2<br>-3<br>-4<br>Monetary Real<br><!-- End of picture text -->

- (C) Impact of rising U.S. long-term yields on EMDE real exchange rate

(B) Impact of rising U.S. long-term yields on EMDE industrial production <!-- Start of picture text --> Percent<br>1.4<br>1.2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>-0.2<br>-0.4<br>Monetary Real<br><!-- End of picture text --> (D) Impact of interest rate shock in four major economies on EMDE capital <!-- Start of picture text --> Percent Percent of GDP, deviation from baseline<br>1.2<br>0<br>1.0<br>0.8<br>0.6 -1<br>0.4<br>0.2<br>-2<br>0.0<br>-0.2<br>-0.4 -3<br>-0.6 t t+4 t+8<br>Monetary Real Quarters<br><!-- End of picture text --> Sources: Haver Analytics, Bloomberg, World Bank. A.B.C. Impulse responses were derived in two steps. First, “real” and “monetary” shocks are identified using a structural vector autoregression with sign restrictions, assuming that an adverse U.S. monetary shock increases long-term yields and reduces stock prices in the United States, while a favorable U.S. real shock increases both yields and stock prices. Second, “real” and “monetary” shocks are included as exogenous regressors in a separate vector autoregression model including EMDE industrial production, long-term bond yields, stock prices, nominal effective exchange rates and bilateral exchange rates against the U.S. dollar. Based on a sample of 23 EMDEs and estimated over the period January 2013-September 2015. D. Figure shows the impulse response of capital inflows to 64 EMDEs, according to a six-dimensional vector regression model linking capital inflows (including foreign direct investment, portfolio investment and other investment as a share of GDP), to quarterly real GDP growth in both EMDE and G4 countries (United States, Euro Area, Japan and the United Kingdom), real G4 short-term interest rates (three-month money market rates minus annual inflation measured as changes in GDP deflator), G4 term spread (10-year government bond yields minus three month money market rates), and the VIX index of implied volatility of U.S. SP 500 options. The 100 basis point shock on the U.S. term spread was applied to the model assuming a range of pass-through rates to Euro Area, U.K. and Japanese bond yields, from zero to 100 percent. Grey area shows the range of estimated effects on capital inflows depending on pass-through rates (the lower bound corresponds to a zero pass-through rate implying a 40 basis points shock to global bond yields, while the upper bound corresponds to a 100 percent pass-through rates, or a 100 basis points shock to global bond yields). In the median case, global bond yields increase initially by 70 basis points.
underprivileged? Are all these constitutions and legal actions, to the extent they are effective at all, covert vehicles for preserving privilege, or should we revise our understanding of the conventional wisdom?

Here we begin to answer these questions. Our curiosity was triggered by a book that carried out detailed studies of SE rights enforcement in Brazil, India, Indonesia, Nigeria, and South Africa (Gauri and Brinks 2008). That book offered the first systematic cross-national survey of SE rights litigation, including descriptions of the cases filed in each country, estimates of the numbers of people benefiting from constitutional health and education rights cases in Brazil, India, Indonesia, Nigeria, and South Africa, and preliminary analyses of the extent to which giving courts a more prominent role in economic and social policy-making on the basis of social and economic rights in fact benefited disadvantaged individuals and groups.

In this paper, we conduct new analyses of the distributive effects of the social and economic rights cases that came out of that five-country survey. The five countries in the sample included common law countries with records of aggressive (India and South Africa) and limited SE rights litigation (Nigeria), and civil law countries with aggressive (Brazil) and incipient (Indonesia) litigation. They included countries with (by global standards) recent and old constitutions, and countries with varying years of democratic experience. Judicial review is abstract and centralized in Indonesia; concrete and diffuse in India, Nigeria, and South Africa; and a blend in Brazil. The countries also vary in levels of national income and state capacity. The survey sought to unearth a complete or representative sample of cases in each country involving the right to health and health care, and the right to education.<sup>1</sup> These two issue areas provide

> 1 In the cases of India and South Africa, this included all cases at the High Court level and above (India 1950-2006, resulting in 382 cases, and South Africa 1994-2006, resulting in 32 cases); in Brazil, it included all electronically reported cases from the highest courts of four states (Bahia, Goiania, Rio de Janeiro, Rio Grande do Sul) plus the decisions of the two apex courts, from 1994-2004, resulting in some 7400 cases; in Indonesia (a unitary country) it

5