rafmacalaba/datause-encoder-data huggingface dataset:
13. Are project implementing agencies required to prepare periodic progress reports on projects? Does this include an update on the cost benefit analysis? Are the sponsoring departments accountable for changes recorded in either costs or benefits and for the delivery of net benefits? What mechanisms exist to ensure that this occurs? Is this record of investment management used in subsequent budget discussions with the MOF or Ministry of Planning?

14. For a representative subset of the public investment program (including Banksupported projects), what is the average percentage cost over-run (in inflationadjusted terms) on major projects in key sectors?

# **7. Facility Operation**

15. Are projects commissioned to private contractors and, if so, are contracts awarded on the basis of competitive bidding? Are international firms permitted to bid on contracts? If other methods are used, describe the methods. Is there any evidence from Country Procurement Assessment Reviews (CPARs) or other reviews of procurement contributing to cost escalation or fraud?

# **8. Basic Completion Review and Evaluation**

16. Is there a process for handover of management responsibility for future operation and maintenance of the created assets to service delivery agencies? Do service delivery agencies have an adequate budget funding to operate and maintain these assets? Is service delivery associated with facility operation tracked through time? Are agencies held accountable for the delivery of services?

17. Does the government maintain an asset register or inventory of public sector property, equipment, vehicles, etc.? Is legal title to assets maintained? Are assets valued according to sound accounting principles, such that the accounting definition of an asset is met, depreciation is deducted from the asset value and where feasible, asset values are updated to reflect changed prices?

18. For a representative subset of the public investment program, what is the delay in project completion relative to initial estimated time and what is the deviation from the original (and amended) budget on major projects in key sectors?

19. Is the actual net present value (NPV) of completed projects measured, and is a project end evaluation undertaken to review the nature of differences relative to the estimated NPV at appraisal? What alternative methods, if any, are used to undertake ex post evaluation of completed projects?

14
In all cases the sign of the nominal interest rates and inflation rate is equal to what was theoretically expected: the nominal interest rates come out as positive and the inflation rate comes out as negative and with an absolute value equal to that of the interest rate. Ihe results confirm the presumption that the demand for real deposits depends on the real interest rate paid on them. The coefficients are significant at the 1% confidence level and do not differ, in the OLS estimations, in absolute value between the two periods, indicating that no significant structural change took place along those 10 postfinancial reform years.

The estimates for the longer period using instrumental variables ,Regression (c), remain highly significant but their absolute values for the interest elasticity are higher than in the OLS estimate. In this case the semi-log interest elasticity with respect to the monthly real interest rate is about 1.1 in the short run and 11 in the long run. These estimates mean that a 10% fall in the demand for deposits requires, for them to be rolled over, an increase of 9 percentage points in the monthly interest rate in the short run and 0.9 percentage points in the long run. Unfortunately, the instrumental variables technique did not yield satisfactory results for the later period, probably because the instruments used could not capture the sharp fluctuations experienced in both nominal interest rates and inflation rates during Ihis period.

In the system we have described above, the real interest rate on time deposits of the institutionalized financial system depends on a delicate equilibrium between expectations of melt downs and the need of the government to refinance its debt with the financial system that is the counterpart of most of the interest earning deposits at the commercial banks.

If we assume that the government controls the rate of devaluation and can always outsmart the market by devaluing by more than what was expected, we arrive to the conclusion that to a certain extent the government determines the ex-post real rate of interest. The ex-post real interest rate in the financial system is basically determined by the only significant creditor of the system: the Central Bank. This is certainly not done on a monthly basis but it is actually obtained through the inevitable melt-downs that systematically take place.

45
restrictions were lifted, India‘s manufacturing has seen large changes in spatial locations and agglomerations (e.g., Fernandes and Sharma 2011).

These changes provide much greater longitudinal variation than could typically be exploited. Micro-data for India‘s organized manufacturing sector extend back to 1989. We prepare our metrics for 1989 similar to those used in 2005. We restrict our sample to districtindustry observations present in both periods. Table 8 estimates a panel specification of the form: ln(Entrydit) = ηit + δdt + πdi + γ∙ln(Incumbent Employmentdit) + γI∙Inputdit + γO∙Outputdit + γL∙Labordit + εdit.

We now include a vector of district-industry fixed effects πdi that control for fixed differences across district-industries; we also extend our earlier fixed effects to be district-year and industry-year controls. These specifications thus employ panel variation: how much of the growth in district-industry entrepreneurship can we explain through changes in incumbent local conditions that are especially suitable for particular industries? By including district-year and industry-year fixed effects, we measure this effect after controlling for general district and industry development between 1989 and 2005.

Table 8 provides strong confirmation for our basic findings. In the first column, growth in general incumbent employment over the 16 years is linked to higher entrepreneurship. The elasticity is half the size estimated in the cross-section work. The elasticity decline may indicate that an upward bias existed in the cross-sectional estimations (e.g., due to an omitted factor), but is also possible that the differencing exacerbated measurement error and its downward bias. In the second column, we also find support for the Marshallian metrics related to input and output markets. The coefficients are slightly larger than in the cross-sectional estimations and precisely estimated. Interestingly, labor conditions do not find support in the panel setting.<sup>15</sup> Changes in the Chinitz metric yielded implausibly large coefficients values due to outliers, and we do not report them. Of our metrics, the Chinitz effect is the most sensitive due to how it embodies both the establishment size distribution and input-output exchanges. Its sensitivity is thus not very surprising.

Overall, the panel estimations strongly support our core evidence on the link between entrepreneurship and local industrial conditions in India. We think that India‘s industrial past, and the government-led spatial allocation of industrial activity that is rapidly becoming undone, provides a very interesting laboratory for testing many features of agglomeration and urban

> 15 One potential factor that may contribute to the greater sensitivity of the labor metric compared to inputoutput measures is that the labor metric builds upon worker flows in the United States which may differ substantially from India. The input-output metrics, by contrast, directly build upon India‘s input-output tables.

24
percent – the agriculture-based countries – are located in the poorest region of the world: Sub-Saharan Africa. Of the 25 countries of the agriculture-based group, 12 are SubSaharan, 4 are from Eastern Europe and Central Asia, 3 from both East Asia and the Pacific and South Asia, and only 2 and 1 from Latin America and the Caribbean and Middle East and North Africa, respectively.

**Figure 3: Population in agriculture and income shares vary across countries**

<!-- Start of picture text --> Burundi<br>Burkina Faso<br>Lao PDR<br>Nepal<br>Tanzania<br>Ethiopia<br>Kenya<br>Madagascar<br>Cambodia<br>Vietnam<br>Bangladesh<br>Uganda<br>Cameroon<br>Yemen, Rep.<br>Kyrgyz Republic<br>Guyana<br>Albania<br>Gambia, The<br>Nigeria<br>Cote d'Ivoire<br>Pakistan<br>Moldova<br>India<br>Ghana<br>Haiti<br>Thailand<br>Georgia<br>Morocco<br>Philippines<br>Guatemala<br>Uzbekistan<br>Kazakhstan<br>Honduras<br>Armenia<br>Azerbaijan<br>Sri Lanka<br>Nicaragua<br>Indonesia<br>Turkey<br>Paraguay<br>Bolivia<br>Tajikistan<br>Peru<br>Mali<br>Macedonia, FYR<br>Guinea<br>Dominican Republic<br>Jamaica<br>Costa Rica<br>Colombia<br>South Africa<br>El Salvador<br>Ukraine<br>Senegal<br>Panama<br>Benin<br>Romania<br>Lithuania<br>Brazil<br>Venezuela, RBChile Agriculture incomes (% of total)<br>Mauritania<br>Poland Agriculture population (% of total)<br>Ecuador<br>Estonia<br>Belarus<br>Hungary<br>Mexico<br>Jordan<br>Russian Federation<br>Bulgaria<br>0 10 20 30 40 50 60 70 80 90 100<br><!-- End of picture text --> Note: authors calculations based on GIDD dataset using developing countries information only.

7
- 20 -

where _s0_ is the share of an outside option _j_ = 0 , which is defined as a choice of consuming beef from intra-EU countries, rather than importing from outside regions. The mean utility level of this outside alternative is normalized to zero. For empirical simplicity, the brandspecific characteristics in Equation (6) are assumed to be represented by the country-specific fixed-effect.

# **_Estimation method and econometric issues_**

Given the demand and supply equations, a three-stage least squares (3SLS) technique is used to estimate the market share and market prices, both of which are jointly determined in Equations (4) and (6). This is a typical approach to the supply and demand system equations (e.g., Greene, 2000; Epple and McCallum, 2006).

In addition to the price-quantity simultaneity, another endogenous problem would be created when per capita GDP data are used as a proxy variable for the shadow price of labor. It is obvious that national income consists of beef export earning, which is dependent on _~~p~~_ * _jt_ and _s jt_ . To deal with this endogeneity problem, the 1-year lagged GDP data are used for _w_ . Although this treatment may not completely solve the underlying endogeneity, it is worth noting that the main estimation results from the data in hand are not changed even if different lags are allowed for.<sup>30</sup> However, even if the lagged value of GDP per capita can be treated as exogenous, one might remain concerned about endogeneity between national income and infrastructure stocks. This is a well-documented empirical problem in the growth literature (e.g., Esfahani and Ramírez, 2003; Fay, Yepes, 2003; Calderón and Servén, 2004). While accumulated capital stocks will allow to promote economic growth, the high level of national income can afford more

> 30 The simple correlation between the lagged GDP per capita and beef exports is -0.04. The export price and quantity are also not correlated with the GDP per capita (0.32 and -0.05, respectively).
_Estimates and Projections of Mortality by Cause_ _82_

- Fiusa Lima, Jose T. n.d. 'Malaria mortality in Brazil-1977-1982.' Paper presented at the Brazilian Congress of Tropical Medicine.

- Frenk, Julio, Jose L. Bobadilla, Jaime Sepfilveda, and Malaquias L6pez Cervantes. 1989. 'Health transition In middle-income countries: New challenges for health care.' _Health Policy and Planning_ 4(1):29-39.

- Ghana Health Assessment Project Team. 1981. 'A quantitative method of assessing the health impact of different diseases in less developed countries.' _International Journal of Epidemiology 10:73-80._

- Hakulinen, T., H. Hansluwka, A. D. Lopez, and T. Nakada. 1986a. 'Global and regional mortality patterns by cause of death in 1980.' _International Journal of Epidemiology_ 15(2):226-233.

- Hakulinen, T., H. Hansluwka, A. D. Lopez, and T. Nakada. 1986b. 'Estimation of global mortality pattems by cause of death.' Pp. 179-205 in H. Hansluwka, A. D. Lopez, Y. Porapakham, and P. Prasartkul (eds.), _New Developments in the Analysis of Mortality and Causes of Death._ Bangkok: World Health Organization and Mahidol University.

- Institute of Medicine. 1986. _New Vaccine Development: Establishing Priorities._ Washington, D.C.: National Academy Press.

- Morrow, R. H. Jr. n.d. 'The application of a quantitative approach to the assessment of the relative importance of vector and soil transmitted diseases in Ghana.' Unpublished paper. Special Programme for Research and Training in Tropical Diseases, World Health Organization, Geneva.

- Omondi-Odhiambo, J. K. Van Ginneken, and A. M. Voorhoeve. 1988. 'Mortality by cause of death in a rural area of Machakos district, Kenya in 1975-1978.' Unpublished paper. Netherlands Institute for Preventive Health Care-TNO, Leiden.

- Omran, Abdel R. 1971. 'The epidemiological transition: A theory of the epidemiology of population change.' _Milbank MemoizI Fund Quarterly_ 49:509-538.

- Parkin, D. M., E. Laara, and C. S. Muir. 1988. 'Estimates of the worldwide frequency of sixteen major cancers in 1980.' _Int. J. Cancer_ 41:184-197.

- Pike, E. G. _1987. Engineering Against Schistosomiasislillharzia: Guidelines Toward Control of the Disease._ London. Macmnillan.

- Preston, Samuel H. 1976. _Mortality Patterns in National Populations, with Special Reference to Recorded Causes of Death._ New York: Academic Press.

- Royston, Erica, and Alan D. Lopez. 1987. 'On the assessment of matemnal mortality.' _Rapp. trimest. statist. sanit. mond._ 40:216-224.

- Walsh, Julia A. 1988. _Establishing Health Priorities in the Developing World._ Boston, Mass.: Adams Publishing Group, Ltd.

- West, Keith P. Jr., and Alfred Sommer. 1987. 'Delivery of oral doses of vitamin A to prevent vitamin A deficiency and nutritional blindness: A state-of-the-art review.' Administrative Committee on Coordination Subcomnuttee on Nutrition, Nutrition Policy Discussion Paper No. 2. Rome: Food and Agriculture Organization.

- World Bank. 1988. _World Development Report 1988._ New York: Oxford University Press.
null of a homogeneous impact of the IHC program on the 75<sup>th</sup> percentile of the clearance time distribution across treated firms.

**Figure 1.  Heterogeneity Tests for Benchmark Synthetic Control Method Estimates**

<!-- Start of picture text --> unadjusted mean adjusted<br>log clearance time log clearance time<br>K-S p-value = 0.60 K-S p-value = 0.09<br>A-D p-value = 0.50 A-D p-value = 0.12<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>75th pct clearance time 75th pct clearance time<br>K-S p-value = 0.01 K-S p-value = 0.73<br>A-D p-value = 0.00 A-D p-value = 0.80<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>90th pct clearance time 90th pct clearance time<br>K-S p-value = 0.14 K-S p-value = 0.33<br>A-D p-value = 0.07 A-D p-value = 0.35<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>log import value log import value<br>K-S p-value = 0.05 K-S p-value = 0.28<br>A-D p-value = 0.14 A-D p-value = 0.43<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>.2 .2<br>0 0<br><!-- End of picture text --> Notes: The figure shows the distribution of percentile rank statistics, pf, for each of four outcome variables, relative to a cumulative distribution function of the uniform distribution function. The first column shows distributions of pf from the benchmark SCM results. The second column shows distributions of pf recalculated after the estimated treatment effects are adjusted by the mean estimated treatment effect (�̅). Formal tests for heterogeneity in each case are either Kolmogorov-Smirnov (K-S) or AndersonDarling (A-D). The p-values for each test are reported in each graph.

# **8.  Conclusion**

Each year hundreds of millions of dollars in development aid are spent supporting trade facilitation reforms. Yet few of these reforms have been subject to formal scrutiny via impact evaluation. Procedural and other reforms by border management agencies are undertaken in 43
inference procedure for each of Hypotheses I-VI, as set out in Appendix Table A.1. We also included a small number of secondary tests based on different outcomes, samples, and/or specifications. In Section 4, we report results for every primary test; secondary tests are in Section 4 or in an appendix. To aid interpretation, we also include a small amount of supplementary analysis that was not discussed in the pre-analysis plan—e.g. impacts of advertised P4P on teacher attributes beyond observable skill and intrinsic motivation, and estimates from a teacher value added model—but are cautious and make clear when this is post-hoc.

# **3 Data**

The primary analyses make use of several distinct types of data. Conceptually, these trace out the causal chain from the advertisement intervention to a sequence of outcomes: that is, from the candidates’ application decisions, to the set (and attributes) of candidates hired into schools, to the learning outcomes that they deliver, and, finally, to the teachers’ decisions to remain in the schools. In this section, we describe the administrative, survey, and assessment data available for each of these steps in the causal chain. Our understanding of these data informs our choices of specification for analysis, as discussed in detail in the pre-analysis plan.

## **3.1 Applications**

Table 1 summarizes the applications for the newly advertised jobs, submitted in January 2016, across the six districts.<sup>19</sup> Of the 2,185 applications, 1,963 come from candidates with a TTC degree—we term these _qualified_ since a TTC degree is required for the placements at stake. In the table, we present TTC scores, genders, and ages—the other observed CV characteristics—for all qualified applicants. Besides these two demographic variables, TTC scores are the only consistently measured characteristics of all applicants.

The 2,185 applications come from 1,424 unique individuals, of whom 1,194 have a TTC qualification. The majority (62 percent) of qualified applicants complete only one application, with 22 percent applying to two districts and 16 percent applying to three or more. Multiple applications are possible but not the norm, most likely because each district requires its own exam. Of those applying twice, 92 percent

> 19These data were obtained from the six district offices and represent a census of applications for the new posts across these districts.

14
Figure 1: Centrality of Fortune 500 Agribusiness Companies <!-- Start of picture text --> 2014 2014<br>2015 2015<br>2016 2016<br>2017 2017<br>2018 2018<br>2019 2019<br>2020 2020<br>2021 2021<br>2022 2022<br>0 20 40 60 80 100 120 0 10 20 30 40 50 60<br>average number of links average number of links<br>US based non-Fortune 500 US Fortune 500 US based non-Fortune 500 US Fortune 500<br><!-- End of picture text -->

**Note:** The graph shows the average number of customer and supplier links (“degree centrality”) for actively covered U.S. Fortune 500 agribusiness companies and other U.S. firms over time. Fortune 500 agribusinesses are identified from the March 2022 list of U.S. Fortune 500 companies. The left graph depicts the degree centrality of actively covered enterprises based on their links to all firms observed in the network in a given year, the right graph depicts the degree centrality of actively covered enterprises while including only links between firms that are constantly observed in the sample (that is excluding any entrants or exiters between 2014 and 2024).

Recent data reveal a strategic shift among U.S. Fortune 500 companies, with a discernible focus since 2018 towards strengthening intra-corporate linkages—particularly ownership ties—over external customer and supplier relationships. This shift towards internal consolidation is clearly illustrated in Figure 2 (left panel), which demonstrates a notable increase in ownership-related ties, all consolidated under the same ultimate parent entity, within these prominent corporations. The trend is visible both at the average (upper left panel) and at the median (lower left panel). While U.S. non-Fortune 500 and agri-food firms from the rest of the world also exhibit an increase in ownership-related affiliations by 2021, the growth in these connections significantly lags behind their expansions in supplier and customer links, especially when analyzed at the median level. This indicates a more subdued inclination toward internal network densification among either smaller corporations or non-U.S. firms.<sup>18</sup> Moreover, the rise in ownership links among U.S. Fortune 500 companies within the agribusiness sector closely tracks their increase in traditional business connections, suggesting a strategic integration of their corporate structure with their primary business operations. In stark contrast, such internal connec-

> 18Analyzing the subset of smaller U.S. corporations in Figure 3 below suggests that the subdued internal network densification is driven by non-U.S. corporations.

16
Economic Parameters of Deforestation 44 ambiguous since the reduction in transportation unit costs and the increase in distancc due to increased logging operate in opposite directions.

An increase in agricultural productivity is modelled as a one-third increase of the agricultural output quantity that can be sold at a fixed price. This assumes infinite elasticity of the demand for the agricultural product, which could be expected for the exports of a homogenous cash crop from a small country. As shown in Migure 9, the increase in yields would lead to an increase in the agricultural area. The resulting timber price increase would shift the managed forest area into the area of unmanaged forests, which would decline. Of course, these effects depend on the assumed characteristics of the agricultural market. If, in the other extreme, demand for the agricultural product was totally inelastic (i.e. for a subsistence crop), the agriculture area would decline with yield increases, the timber price would fail, and the pressure on unmanaged forests would be reduced.

Figurc 10 shows a situation in which no managed forestry exists. This scenario helps understand the effect of forest plantations on urunanaged forests. Without managed forests, timber is a non-renewable resource with increasing extraction costs. As a result, the price path shows an increasing rate of price increase. In the short-run, the introduction of managed forests increases logging of unmanaged forests since managed forests create additional demand for land. The long-run effect, however, is different. Without managed forests, timber prices would rise until all unmanaged forests arc (at least asymptotically) depleted. With managed forests, a cap is put on the rise of timber prices at the level at which all demand can be supplied from managed forests. When this price level is reached, it will not be profitable to log remaining unmanaged forests. Hence, the introduction of managed forests increases the area of unmanaged forests that is ultimately preserved.

A scenario of quadrupling the decision maker's discount rate is presented in order to analyze the effects of different tenure regimes on land use patterns. Figure 11 shows the