rafmacalaba/datause-encoder-data huggingface dataset:
Table 4: Decompositions of urban share changes, 1994-2005

|||Total Activity||O|rganized Sect|or|Un|organized Se|ctor|
|---|---|---|---|---|---|---|---|---|---|
||Plants|Employ.|Output|Plants|Employ.|Output|Plants|Employ.|Output|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|<br>A. Sector change in urbanization le|vel using bala|nced panel||||||||
|Urban share start|0.247|0.376|0.615|0.688|0.667|0.620|0.239|0.302|0.565|
|Urban share ending|0.289|0.395|0.528|0.595|0.567|0.514|0.279|0.347|0.589|
|Urban share change|0.042|0.019|-0.087|-0.093|-0.100|-0.106|0.041|0.045|0.024|
|B. Decomposition: Bailey et al. (19|92)|||||||||
|Within-district component|0.045|0.022|-0.074|-0.095|-0.086|-0.091|0.047|0.057|0.010|
|Between-district component|0.030|0.029|-0.001|-0.014|-0.009|-0.001|0.024|0.014|-0.016|
|Covariance term|-0.033|-0.032|-0.011|0.015|-0.005|-0.014|-0.030|-0.025|0.030|
|Total|0.042|0.019|-0.087|-0.093|-0.100|-0.106|0.041|0.045|0.024|
|C. Decomposition: Griliches and R|ejev (1995)|||||||||
|Within-district component|0.029|0.006|-0.080|-0.087|-0.089|-0.098|0.032|0.044|0.025|
|Between-district component|0.013|0.013|-0.007|-0.006|-0.012|-0.008|0.009|0.001|-0.001|
|Total|0.042|0.019|-0.087|-0.093|-0.100|-0.106|0.041|0.045|0.024|

Notes: Table decomposes changes in urban shares. Column headers indicate metrics and time periods. Panel A presents the urbanization change using a balanced panel of districts employed in the decomposition. Decomposition technique follows Foster et al. (2001), Baily et al. (1992), and Griliches and Regev (1995). For the Bailey et al. (1992) technique, the within component represents changes in urban shares within districts with districts weighted by initial employment shares for the Indian economy. Positive values indicate that districts tended to have increasing urban shares when weighted by initial employment. The between component represents changes in employment shares across districts interacted with the initial deviation of districts from the national urban share. Positive values indicate that employment tended to be reallocated towards districts that had higher initial urban shares. The covariance component term represents the interaction of changes in urban shares for districts across the period with changes in employment shares for districts across the period. Positive values indicate that fast-growing districts also experienced rising urban shares. The three components by definition sum to the total change in urban share for India, with some minor deviations due to panel composition changes. Appendix Tables 1a and 1b present the decompositions for the 1994-2000 and 2000-2005 sub-periods, respectively.
Mattoo, Aaditya, Z. Wang and S-J Wei, 2011, ―Tracing Value-Added in International Trade: An Overview of Issues and a Proposal,‖ Mimeo, The World Bank.

Maddison, Angus, 1982, _Phases of Capitalist Development_ , Oxford University Press.

- Naughton, Barry, 1995, _Growing out of Plan: Chinese Economic Reform 1978–1993_ . Cambridge: Cambridge University Press.

- North, Douglas, 1981, _Structure and Change in Economic History_ , New York: W.W. Norton.

- North, Douglas, 1990, _Institutions, Institutional Change and Economic Performance_ . , Cambridge: Cambridge University Press.

- OECD, 2010, ―Beyond the DAC:  The Welcome Role of Other Providers of Development Co-Operation,‖ DCD Issues Brief May 2010, OECD: Paris.

Perkins, D. H., 1969, _Agricultural Development in China, 1368–1968_ . Chicago: Aldine.

- Pleskovic, Boris, 1994,  ̳Financial Polices in Socialist Countries in Transition‘. World Bank Policy Research Working Paper Number 1242. Washington, DC: World Bank.

- Prebisch, Raul, 1950, _The Economic Development of Latin America and its Principle Problems_ , United Nations:  New York.

- Pritchett, Lant, 1997, ―Divergence, Big Time,‖ _Journal of Economic Perspectives_ , Vol. 11, No. 3, pp. 3- 17.

- Rana, P. and N. Hamid, 1995, _From Centrally Planned to Market Economies: The Asian Approach. Volumes 1–3_ . Hong Kong, Oxford, New York: Oxford University Press.

- Ravallion, Martin, 2011, ―Knowledgeable Bankers? The Demand for Research in World Bank Operations,‖ World Bank Policy Research Working Paper Number 5892.

- Ravallion, Martin and Adam Wagstaff, 2010, ―The World Bank‘s Publication Record,‖ World Bank Policy Research Working Paper Number 5374.

- Rodrik, Dani, 2005,  ̳Growth Strategies‘. In P. Aghion and S. N. Durlauf (eds), _Handbook of Economic Growth. Volume 1, Part A_ . Amsterdam: Elsevier Science Publishers (North-Holland), 967–1014.

- Roubini, Nouriel and Xavier Sala-i-Martin, 1995, ―A Growth Model of Inflation, Tax Evasion and Financial Repression, _Journal of Monetary Economics_ , Vol. 35(2), pp. 275-301.

- Rogers, Halsey. 2010.  ―The global financial crisis and development thinking,‖ World Bank Policy Research Working Paper Number 5353.

Romer, Paul M., 1990, ―Endogenous Technological Change,‖ _Journal of Political Economy_ , Vol. 98.

Sachs, Jeffrey. 1993. _Poland’s Jump to a Market Economy_ , MIT Press: Cambridge, MA.

- Sachs, J. D., W.T. Woo, and X. Yang, 2000,  ̳Economic Reforms and Constitutional Transition‘. _Annals of Economics and Finance_ , 1, 435–91.

51
Edwards, Sebastian. 1996. “Exchange Rate Anchors, Credibility and Inertia: A Tale of Two Crises, Chile and Mexico.” American Economic Review, 86,2: 176-180.

Edwards, Sebastian and Alejandra Cox-Edwards. 2000. “Economic reforms and labor markets: policy issues and lessons from Chile.” National Bureau of Economic Research. Working Paper Series (U.S.); No. 7646:1-66, Boston, April 2000.

Evans, D.C. and B. Jovanovic. 1989. “An Estimated Model of Entreprenurial Choice under Liquidity Constraints.” Journal of Political Economy 97:4 pp 808-826.

Gil-Diaz, Franciso and Agustin Carstens. 1996. “One Year of Solitude: Some Pilgrim Tales about Mexico’s 1994-1995 Crisis.” American Economic Review, 86,2: 164-169.

Hamilton, Jonathan, Jacques-François Thisse and Yves Zenou. 1998. “Wage Competition with Heterogenous Workers and Firms.” Centre for Economic Policy Research. Discussion Paper Series (U.K.); No. 2141:1-22, May 1999.

Helpman, Elhanana and Assaf Razin (1987) Exchange Rate Management: Intetermporal Trade-offs, “ American Economic Review, 77:107-123.

Johansen, Soren. 1988. “Statistical Analysis of Cointegrating Vectors.” Journal of Economic Dynamics and Control (Netherlands); 12:231-54 June-September 1988.

Johansen, Soren and Katarina Juselius. 1992. “Testing structural hypothesis in a multivariate cointegration analysis of PPP and UIP for UK.” Journal of Econometrics, 53, 169-209.

Johansen, Soren and Katarina Juselius. 1994. “Identification of the long-run and short-run structure. An application of the ISLM model.” Journal of Econometrics, 63, 7-36.

Kravis, Irving B. and Robert E. Lipsey. 1983. “Towards an explanation of National Price Levels.” International Finance Section, Department of Economics, Princeton University.

Maloney, W.F. 1999. “Does Informality Imply Segmentation in Urban Labor markets? Evidence from Sectoral Transitions in Mexico.” The World Bank Economic Review 13:2 275-302.

_______ 1998a. “The Structure of Labor Markets in Developing Countries: Time Series Evidence on Competing Views,” IBRD Working Paper 1940, Latin America and the Caribbean Region, Poverty Reduction and Economic Management Unit, World Bank, Washington, D.C. Processed.

_______ 1999. “Self-Employment and Labor Turnover: Cross-Country Evidence. The Structure of Labor Markets in Developing Countries: Time Series Evidence on Competing Views.” IBRD Working Paper 2102, Latin America and the Caribbean 27
takes time and whose effects are spread out over time. For instance, with such data, duration models could be tested to study the employment and unemployment spells of workers following migration. It would also be highly desirable for researchers to have access to datasets incorporating an economically relevant and sufficiently fine _spatial identifier_ that would enable researchers to better study the workings of local labor markets (since interactions probably occur at a small geographic level). Such data would also enable the matching of different sources and enable researchers to better take into account the local contexts of both origin and destination areas. In this respect, surveys with information on both areas of origin and areas of destination (for instance village studies matched with a sample of migrants originating from the area) should prove very useful. Building such datasets is costly but it is important to gain a sufficiently fine understanding of the migration process to make it beneficial.

Without being exhaustive, the following topics emerge as important for future research:

- (i) There is a need to identify _which individual, contextual, or even institutional factors can make migration succeed_ or fail. The role of education in accelerating the assimilation of migrants to the labor market has been shown. It remains to be investigated whether education acquired in  the place of origin or in the place of destination is more helpful, and how the assimilation of uneducated workers could be enhanced.

- (ii) Another important issue concerns the _minimum level of urban public services_ which should be provided to migrants, considering that public goods are congestible, that migrants may not have the capacity to finance their shares, but that public services can be key in initiating successful assimilation.

- (iii) Research is also needed to investigate which _types of labor-market intermediation_ would be more efficient in matching the rural supply and the urban demand for labor. This would involve studying in more detail how migrants find their jobs but also the impact of job-search methods on the occupations they find. One related issue would be whether migrants are

51
Over 90% of population continues to have at most one of the key assets.

Figure 5: Correlation analysis household assets ownership and welfare across SEG <!-- Start of picture text -->
-.............-  - - - -,-,-.-.7..  7<br>~0.9<br>...  C.  st-9Cnsi-98<br>S EG-98<br>Wage  Wage  Commerce  Others  Export  Sub.  Inactives<br>Public  p riva te  Ac tive s  Fa  rme  rs  Farmers<br><!-- End of picture text -->

Figure 6: Correlation analysis household assets ownership and welfare across regions <!-- Start of picture text --> 0.8<br>\,/ : ~~~~~~~~Reg-9<br>Cnst-98<br>| eReg-98<br>0.4<br>Ouest Sud- Centre- Centre- Nord Ouaga- Autres Sud-Est<br>Sud Nord Bobo Villes<br><!-- End of picture text -->

18
read directly from the bill (Table 1). Second, a further 30% of households were unwilling or unable to show their utility bills to the interviewer, but were able to recall the value of their most recent monthly bill. In these cases, the local utility tariff structure was applied to the reported expenditure in order to infer the physical consumption of the service. For the remaining 35% to 45% who neither presented bills nor recalled expenditure, imputation techniques were used to infer expenditure based on household characteristics.

3.6 Some evidence of selectivity effects was found with regard to the sub-sample that provided coherent information on household expenditure. Both for water and electricity, high-income households were more often able to report expenditure. In the case of water, this may simply reflect higher rates of service coverage in the upper income quintiles. However, in the case of electricity, where coverage is practically universal, this explanation is no longer relevant.

**Table 1: Summary of data availability on utilities expenditure**

||**Water**|**Electricity**|**Gas**|**Telephone**|
|---|---|---|---|---|
|Percentage of households that showed bill|27.9|35.4|26.5|23.7|
|Percentage of households that verbally reported expenditures|29.7|29.8|30.4|28.7|
|Percentage of households that did neither of the above|42.4|34.8|43.1|47.6|
||100.0|100.0|100.0|100.0|

_Source:_ OPSM, May 2002 3.7 Nonetheless, these data limitations in practice do not materially circumscribe the conclusions of this analysis. In reality, expenditure data were only used to evaluate the efficacy of existing social policies in the Metropolitan Area (for the cases of water, sewerage, electricity, and public transport) and Patagonia (for the case of natural gas). The analysis of social policies for water and electricity in the provinces is based solely on the socioeconomic characteristics of the households, without reference to expenditure levels. Furthermore, expenditure data were not used at all in the simulations of alternative social policies, which are based entirely on normative criteria for subsistence consumption, or depend solely on the socioeconomic characteristics of the household.

# **ANALYTICAL TOOLS**

3.8 Using data from the 2002 survey, it is possible to identify the beneficiaries of current social policy mechanisms in the infrastructure sectors, and evaluate how well targeted they are. This is done by examining the extent to which they reach households that live under the official poverty (and extreme poverty) lines, which currently stand at US$65.7 (and US$27.7) per adult equivalent per month. In a similar fashion, it is possible to identify the impact of applying alternative social policy instruments, and examine their pattern of incidence.

3.9 The evaluation of the targeting properties of current and potential, future social policy instruments are based on a number of standard indicators adapted from the income 14
_Source:_ World Bank’s World Development Indicators, July 25, 2023, update.

_Note:_ Unemployment refers to the share of the total labor force that is without work but available for and seeking employment. Youth Unemployment is similarly defined for the share of the total labor force ages 15–24.

Even among those with employment, many find themselves in low paid, informal jobs, and would like to do better. Changes in the structure of the economy and job opportunities due to automation, climate change, and lasting impacts of the COVID-19 pandemic are thought to have made the challenge even harder, resulting in headlines such as “Robots Pose Big Threat to Jobs in Africa, Researchers Warn” (Ridgwell, 2018), “Rising heat stress could destroy 80 million jobs by 2030, UN says” (Taylor, 2019), and “This Chinese jobs crisis could be its worst” (Chen, 2023).

Faced with these current employment challenges and such forecasts, governments face pressure to help job-seekers. One viewpoint is that the problem is a skills mismatch, where many of those seeking jobs do not have the skills sought by employers. This may be due to poor education systems, as well as changes in skills demanded by employers as economic growth, technological change, globalization, and the desire for a green transition change the structure of the economy. A popular solution is then for the government to provide _job training_ so that jobseekers can acquire these skills. An alternative viewpoint is that even when workers have skills that employers want, they have difficulty finding the right job fit due to search and matching frictions. Fragmented and largely informal labor markets may make it difficult to identify job openings, and workers without much work experience may not know how best to look for jobs or signal their skills to potential employers. This results in governments providing a range of _job search assistance_ policies designed to help jobseekers better use the skills they do have.

This paper asks whether, when, and how developing country governments should undertake job training and job search assistance policies. Job generation will typically require policies that boost the demand for labor by increasing firm productivity and overall economic growth. Supply-side interventions that train workers and help them look for jobs will not be very effective if there are few jobs for them to look for. An earlier generation of critical reviews and meta-analyses of the first generation of evaluations of these programs found the typical impacts were rather small, with typically only 2 or 3 people out of every 100 trained or assisted finding work as a result of these programs (McKenzie, 2017). As a result, Blattman and Ralston (2015) argued that “it is hard to find a skills training program that passes a simple cost-benefit test.” 3
Table 7. Two Stage Least Squares for Likelihood of Employment at the Sub-Region Level, Nepal DHS, 1996-2006

||_Lin_|_ear Forest Instrum_|_ent_|_Bin_|_ary Forest Instru_|_ment_|
|---|---|---|---|---|---|---|
||_(1)_|_(2)_|_(3)_|_(1)_|_(2)_|_(3)_|
|Interaction Terms (reference=conflict_1<br>|996)<br><sup>*</sup>||||||
|Conflict_2001|0.803|-6.672|15.331|0.234|-4.359|4.486|
||(0.457)|(4.073)|(10.535)|(0.359)|(3.017)|(5.210)|
|Conflict_2006|0.091<sup>***</sup>|-10.595<sup>*</sup>|2.432<sup>***</sup>|0.053<sup>***</sup>|-6.889|1.194<sup>**</sup>|
||(0.021)|(6.298)|(0.828)|(0.018)|(4.676)|(0.503)|
|Education (reference=no schooling)|||||||
|Some or all primary school|0.255|2.328|-0.499|-0.505|1.282|-0.730<sup>**</sup>|
||(0.706)|(1.965)|(0.529)|(0.549)|(1.437)|(0.321)|
|Some secondary school|0.903|10.249<sup>*</sup>|0.243|0.326|6.752|0.030|
||(0.594)|(6.108)|(0.752)|(0.462)|(4.525)|(0.465)|
|Completed secondary school+|-1.722|14.473|-1.581|-0.709|9.304|-0.488|
||(1.073)|(9.173)|(1.875)|(0.836)|(6.777)|(1.085)|
|Age (reference=age<=20)|||||||
|20<age<=35|0.368|6.085<sup>*</sup>|0.140|0.262|4.136|0.205|
||(0.342)|(3.452)|(0.529)|(0.264)|(2.551)|(0.350)|
|age>35|1.346<sup>*</sup>|-0.671|0.881|0.632|-0.226|0.418|
||(0.757)|(1.029)|(1.103)|(0.586)|(0.717)|(0.646)|
|Socioeconomic status|YES|YES|YES|YES|YES|YES|
|Household composition|YES|YES|YES|YES|YES|YES|
|Year and sub-region dummies|YES|YES|YES|YES|YES|YES|
|Wald χ<sup>2</sup>test|3349<sup>***</sup>|467<sup>***</sup>|1447<sup>***</sup>|5518<sup>***</sup>|1121<sup>***</sup>|3120<sup>***</sup>|
|R<sup>2</sup>|0.987|0.908|0.970|0.992|0.962|0.986|
|N|43|43|43|43|43|43|

Notes: Weighted to national level with weights provided by the Nepal DHS in each year. Standard errors in parentheses. The notation<sup><u>***</u></sup> is p<0.01, ** is p<0.05, * is p<0.10. The first three regressions instrument for conflict with a linear forest variable interacted with year dummies; the last three regressions replace this linear variable with a binary variable for more- or less-forested. Model (1) measures conflict as total mortality; Model (2) measures conflict as husbands migrated; and Model (3) measures conflict as women divorced, separated, widowed, or alone. Source: Authors‟ calculations based on MHP/NE/MI (2007), MH/NE/ORC (2002), and Pradhan _et al._ (1997).

41
14 timely opportunity to estimate welfare and trade reduction indexes. The database contains consistent estimates of annual nominal rates of assistance (NRAs) to the agricultural sector and the same number of consumer tax equivalents (CTEs) for 75 countries over a time period between 1955 and 2007 (Tables 1 and 2). The series contains data at the commodity level, for a sub-set of agricultural products (called covered products) that account for around 70 percent of total agricultural production in the focus countries, which in turn account for 92 percent of global agricultural GDP. Aggregate NRAs and CTEs for various sectors and sub-sectors (including import-competing and exporting sub-sectors) are estimated, using as weights the values of production and consumption, respectively, at undistorted prices.<sup>9</sup> The range of measures included in the Agricultural Distortions database NRA estimates is wide. By calculating domestic-to-border price ratios the estimates include assistance provided by all tariff and non-tariff trade measures, plus any domestic price support measures (positive or negative), plus an adjustment for the output-price equivalent of direct interventions on inputs. Where multiple exchange rates operate, an estimate of the import or export tax equivalents of that distortion are included as well. The range of measures included in the CTE estimates include both domestic consumer taxes/subsidies plus trade and exchange rate policies, all of which drive a wedge between the price that consumers pay for each commodity and the international price at the border.

The most aggregated summaries of NRA and CTE estimates for covered products for developing and high-income countries are presented in Tables 1 and 2. These support the 9 Estimates of the NRA for total agricultural production in the focus countries are obtained by making ‘guesstimates’ of the rates of assistance for the remaining 30 percent of agricultural production. Those guesstimates are not used in the present study, but their impact can be seen by comparing the third and fourth sets of rows of NRAs in Table 1.
## _Box 1: Examples of Partial Performance Indicators_

_Figure i: Container Vessel Delay in Central American Ports_

**_Ship Delay_ :** This measure reflecting the availability of berth and gangs is calculated by subtracting the original scheduled time of the vessel’s arrival at the port from the time the vessel arrives at the berth (second line tied) and is ready to work. Zero delay is ideal, but a delay of up to four hours can be absorbed in the vessel’s itinerary.

<!-- Start of picture text --> 20<br>15<br>10<br>5<br>0<br>Source: Adapted from Kent (2011)<br>Hours<br><!-- End of picture text --> <!-- Start of picture text --> Figure ii: Ship Productivity for Calls Involving Moves<br>between 500 and 1000<br><!-- End of picture text -->

**_Ship Productivity_ :** Probably the most commonly used measure of terminal performance, ship productivity is based on the number of moves per hour during a vessel’s net berth time (see Figure 1). Net berth time is measured from the time the first gang appears on the vessel to the departure of the last gang from the vessel. Ship productivity is calculated by dividing the number of moves by net berth time measured in hours (moves/hour).

<!-- Start of picture text --> 80<br>60<br>40<br>20<br>0<br>Source: Adapted from Kent (2011)<br>Moves/Ship-hour<br><!-- End of picture text --> Efficiency is a relative concept that requires a clear definition of a benchmark, in order for operators to be compared among themselves and against their own performance over time (Liu, 2010). It can be defined in several ways, each serving a different purpose. Economic efficiency is achieved when resources are used in a way that production is maximized at the lowest cost. Allocative efficiency is achieved when production is at the level desired by society and the marginal benefit of the last unit produced equals its marginal cost. Lastly, technical efficiency, a pre-requisite for economic efficiency, is when a firm is producing the maximum output with the lowest quantity of inputs required.

Taking into account the various concepts and indicators of efficiency and performance, their strengths, drawbacks and computational challenges, in this paper we benchmarked technical efficiency by using an approach widely used in the port performance literature, the estimation of technical efficiency frontiers. For that purpose, the database compiled for this paper feeds an econometric estimation that assesses the inputs determining port throughput levels, including all physical assets required for port operations.

# **b. Approaches to Technical Efficiency Frontiers**

The two main approaches used to calculate technical efficiency are Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA); both rely on the estimation of an efficiency frontier. The frontier is determined by the best possible performance drawing on information from the sample.

5