rafmacalaba/datause-encoder-data huggingface dataset:
# **Appendix to “Estimating the Impact of Weather on Agriculture”**

# **A Details on Remote Sensing Weather Data**

## **A.1 On Using Remote Sensing Products for Economics**

Uncertainty is present in all model outputs, and weather data sets are no exception. Spatial data sets of weather variables, like precipitation and temperature, that are produced using remotely sensed data, are not direct measurements of the variable of interest. Satellite sensors provide spatially continuous observation of reflectance from the earth’s surface in different parts of the magnetic spectrum. These values are used to estimate related phenomena, such as cloud presence, cloud top temperature or earth surface temperature. The continuous data sets are then used in combination with directly observed, but often sparsely distributed, gauge data to produce weather variables. Some inputs are common across products, but there are differences in other inputs as well as modeling techniques.

The type of analysis matters in assessing weather data sets for use in economic research. Is the goal to understand climate trends, capture characteristics of a particular agricultural season, or identify extreme weather events occurring in near real-time? This can help determine the relative importance of different data set characteristics, such as spatial detail, temporal frequency and length of record, with respect to the intended analysis. The data sets used in this analysis were constrained by certain minimum criteria, leading to elimination of some commonly used data sets, such as the product from the Center for Climatic Research at the University of Delaware. We also did not consider proprietary data sets, preferring to use sources currently in the public domain. Despite the exclusions imposed by our minimum criteria, the data sets summarized in Table 1 represent a range of spatial resolutions and model types commonly used by economists. Further details on the specifics of each remote sensing product are provided below with the goal of providing economists with direction to a data set that meets the requirements of their analysis.

### **A.1.1 Africa Rainfall Climatology version 2 (ARC2)**

ARC2 is a merged gauge data and remote sensing product that provides daily rainfall outputs for the African continent. The data set, produced by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) provides improvements over ARC1 and a longer length of record compared to the rainfall estimate (RFE), the operational data set of USAID’s Famine Early Warning Systems Network (FEWSNET) program. Inputs are Global Telecommunications System (GTS) rain gauge data over Africa, geostationary Meteosat infrared (IR) imagery, and polar-orbiting microwave Special Sensor Microwave Image (SSM/I) and Advanced Microwave Sounding Unit (AMSU-B).

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log of) country i's market size in year t, _Log GDPi,t_ (in constant 1995 US dollars), which should affect _Duties, Tariff,_ and _Closure_ in line with conventional expectations.

_Income._ Income is one of the most important determinants of trade flows, if not trade policies<sup>2</sup> ". High income is also a statistically significant predictor (though not the only one) of removal from US GSP eligibility (Ozden and Reinhardt [2002]). In order to limit the potential for spurious inference about the effects of GSP, we control for _Log Income,,t_ (using per capita GDP in constant 1995 US dollars).<sup>2 2</sup> _Geography._ A country's distance from important suppliers and markets affects transport costs and thus trade levels, as gravity model studies have repeatedly shown (Leamer and Levinsohn [1995]). In addition, such geography-induced transport costs may serve as a substitute for policy-created import barriers. In contrast to the usual pairwise gravity model, however, we control for location using a country-specific geographical indicator. Specifically, Gallup and Sachs [1999] give the proportion of a country's population that lives more than within 100 kilometers of a coast or navigable river (here, _Landlocked,)_ - though their data are not time-varying. The proportion of "landlocked" population in the dataset's average country is 0.39.

_Growth._ The business cycle is often said to affect trade policy. Protectionist pressures are often greatest during economic downturns (Dornbusch and Frankel [1987] and Rodrik [1995]). Yet severe recessions also may catalyze reform, while prolonged growth may retard it (Rodrik [1994]). For that reason, we control for real GDP growth (Growth1,t) in our analyses (World Bank [2001b]).

# 5 Econometric Models

We estimate several sets of regressions, comparing countries still eligible to those withdrawn from the US GSP program. The first set (models 1, 2, and 3) concerns GSP status as a dummy variable, thereby permitting use of the entire 1976-2000 period. We lag all explanatory variables by one year (except _Landlocked)_ as a first-cut method of addressing concerns about endogeneity.<sup>23</sup> For robustness, we estimate the same model separately for each of the three primary measures of the dependent variable. Hence, if Yi,t is either _Duties,t, Tarnff,,t,_ or _Closure,,t_ for country i in year t then the estimated equation is _Y.Nt_ = _Ce_ + 51 _GSPI,- 1 +_ ,62 _Rhendt.I + 833IMF,,t- 1 + 14 (Log GDP1,t-1 )_ (2) +135 _(Log Income,,t-) + /B6Landlocked, + / 7Growth,,t-j + e,,t._

> 21According to Baier and Bergstrand [2001], it is the most important deterninant.

> 22The source for GDP and per capita GDP figures is World Bank [2001b].

> 23We set _GSP,,t,1_ = 1 for each country's first year in our dataset. (Recall that the sample begins the first year a country is eligible for GSP.)

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WPS4170

# **The "How to" of Fiscal Sustainability**

**A Technical Manual for Using the Fiscal Sustainability Tool**<sup>**1**</sup>

Luca Bandiera, Nina Budina, Michel Klijn and Sweder van Wijnbergen<sup>2</sup>

## **Abstract**

Fiscal sustainability analysis is an important component of macroeconomic analysis for many developing countries. To further enhance understanding of fiscal policy and the constraints faced by policy makers, we develop a toolkit for fiscal sustainability analysis (FSA) in middle-income countries, which builds on previous work in this area and on new developments in dealing with uncertainty. The FSA toolkit includes an excel-based FSA tool and a technical manual accompanying it. The FSA tool is standardized and simple, but at the same time flexible enough to allow for user-defined country specifics. This manual provides step-by-step technical instructions for running the FSA tool, and includes mathematical appendices and a glossary.

## World Bank Policy Research Working Paper 4170, March 2007

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 A companion background paper, published as WPS 4169 surveys various FS approaches that have been incorporated in the FS tool and presents an application of this tool for Turkey.

> 2 First and second author: World Bank, Washington DC, USA, third author: HEAS BV, Netherlands, fourth author: University of Amsterdam, Netherlands.
# The Size and Growth of Govemment Spending

## by David L Lindauer

I. Measuring the Growtn in Governm ent Expendi:'ires ................................................... 3 A. Measuremnent Issues ............................................................. 3 B. OECD Experience ............................................................. 9 C. Developi Nation Experience ............................................................ ng 11 1I. Explaining the Growth in Government Expenditures ................................................. 19 A. "Cost-Accounting" ............................................................ 19 B. Demand-Side Arguments ............................................................ 21 C. Supply-Side Factors ............................................................ 23 D. Development Theorizing ............................................................ 25 Notes ............................................................ 27 Bibliography ............................................................ 30 Tables ............................................................ 32

## David L Lindauer is an Associate Professor in the DeparLnent of Economics, Wellesley College.
Figure 6: Backyarders as a function of CBD distance <!-- Start of picture text --> 0.7<br>0.6<br>0.5<br>0.4<br>0.3<br>0.2<br>0.1<br>0<br>0 5 10 15 20 25 30 35 40 45<br>Distance to CBD<br>Number of Bacakyarders<br><!-- End of picture text --> 28
18 most successful year in which 47 percent of privatization targets were met (Oxford Analytica, March 29, 2005). Meanwhile more than 40 percent of the country’s capital stock is still stateowned (McKinsey India study 2001). At the sub-national level as well there are a large number of enterprises in sectors such as manufacturing, agro-processing, power, and transport which continue to remain in state hands.

# _Europe and Central Asia_

32. State enterprises are playing substantially less of a role in Europe and Central Asia compared to the 1990s. By 2003, all but two countries in the region had completed or were on the verge of completing small-scale privatization, while 20 countries had privatized at least 25 percent of large enterprises. The private sector’s share of GDP by 2003 grew to more than 50 percent in 22 countries, compared to only nine in 1994, with eleven of the 22 countries at 70 percent or more (World Bank 2004).

33. Yet, many countries, including EU accession countries with longstanding privatization programs, e.g. Poland, still have large “strategic” companies in competitive sectors such as steel, petrochemicals, and manufacturing that are state owned. State ownership is especially pervasive in Central Asia: in 2002 state enterprises accounted for over 50 percent of GDP in Belarus, Moldova, Tajikistan, Turkmenistan, and Uzbekistan (World Bank 2004). In the Balkans, countries such as Kosovo and Serbia have thousands of “socially-owned” firms. Residual government ownership in privatized enterprises in the region as a whole is also quite high (Lieberman 2003). And across the region, despite recent advances in sectors such as telecoms, there is still a large stock of utilities (power and water in particular), banks, and nonbank financial institutions such as insurance companies that are still state-owned **.**

# _Latin America_

34. Privatization has been big business in Latin America. But the activity has been concentrated in the three largest countries-- Argentina, Mexico, Brazil--and a handful of smaller ones such as Bolivia and Peru. Indeed, these countries have substantially reduced the role of state enterprises: in Mexico, for example, the share of public enterprises in GDP went from nearly 15 percent in 1982 to less than 5 percent in 2001 (Box 3). But in most other countries in the region, state enterprises are still in operation.
agricultural investment and land productivity on household welfare but also implies that exploring agricultural activities in more detail will be appropriate.

3.2 Agricultural activities and Rand tenure arrangements Data on agricultural production activities in the bottom panel of table 1 illustrate that the average land holding per household is, with 1.01 ha on 2.36 plots (or 0.18 ha per capita), very small, with regional variations (from 0.51 ha in Tigray to 2.25 ha in predominantly pastoral areas). Only 22% of households reported that their current holding allows them to obtain food self-sufficiency and 39% consider land shortage to be the major constraint to increased agricultural production, suggesting that expanding the effective land area through land-related investment should indeed constitute an attractive option. 71% report having one or more oxen, something less dominant (with 45%) in the South where hoe culture and perennial cropping systems dominate. 35% of farmers participated in the government sponsored extension program which is linked to the provision of improved seed, fertilizer, and chemicals - which are used by 37%, 13% and 10% of households, respectively. Land productivity, at about 170 US$/ha (1458 ETB/ha) on average, is lowest (123 US$) in the Southem regions and highest in (288 US$) in Tigray.

Information on subjective land rights perceived by the farmers, their land tenure preferences, as well as actual and hypothetical investrnent in land improvements in table 2 suggests not only that tenure security remains low but also that most farmers would prefer higher levels of land tenure security. Although many producers have undertaken land-improving investment, a surprisingly large share declares that they would change their fanming practices and undertake more investments if land tenure were changed to provide more tenure security to cultivators.

In the 1991-98 period, 9% of the farmers nationally and 18% in Tigray and 21 % in Amhara were affected by land redistribution. Although there is an intent for policy to discourage such practices, there is neither a law nor a clear policy statement at the national level to eliminate or prohibit land redistribution. In fact, only 27% of farmers are confident that there will not be a land redistribution in the future and 9% expect one to happen within the next 5 years. 23% report to have conflicts with local authorities that revolve around land redistribution, again illustrating that tenure insecurity in Ethiopia remains high. With respect to transfer rights, we note that more than 91% of farmers indeed perceive the right to rent or sharecrop whereas 23% indicated that they would be able to temporarily mortgage their land and 4% indicated that they would be able to permanently transfer the rights to their land through sale.

Given the high levels of tenure insecurity and restricted transfer rights, it is not surprising to find strong support for more secure rights; in fact 79% of farmers nation-wide (83% and 84% in Tigray and Amhara) indicate that they would prefer an alternative to the current tenure system. Of these, 48% (61% in Tigray) 12
# **Table 2. Changes in GDP Growth Across the Business Cycle on Public Consumption: Elasticities from Fixed Effects and IV Regressions for Emerging and Advanced Economies**

|VARIABLES|(1)<br>Emerging<br>economies -<br>FE|(2)<br>Advanced<br>economies -<br>FE|(3)<br>Emerging<br>economies -<br>IV|(4)<br>Advanced<br>economies -<br>IV|
|---|---|---|---|---|
|GDP Growth * Exp|1.12<br>[0.136]***|0.37<br>[0.109]***|1.10<br>[0.143]***|0.40<br>[0.091]***|
|GDP Growth * Rec|0.43|-0.22|0.36|-0.24|
||[0.244]*|[0.129]|[0.249]|[0.141]*|
|Lagged Public Consumption Growth|-0.05|0.30|-0.05|0.30|
||[0.054]|[0.096]***|[0.054]|[0.102]***|
|Lagged General Government Expense Growth|0.05|0.04|0.05|0.04|
||[0.034]|[0.065]|[0.047]|[0.058]|
|Constant|0.01<br>[0.006]*|0.01<br>[0.003]***|||
|Observations|800|432|793|418|
|R-squared|0.122|0.158|||
|Number of countries|39|18|39|18|
|Country Fixed Effect|Yes|Yes|Yes|Yes|
|Adjusted R-squared|||0.071|0.112|
|**First Stage IV Estimates**|||First Stage|First Stage|
|Trade Weighted Growth * Exp|||1.17<br>[0.03]***|1.27<br>[0.02]***|
|Trade Weighted Growth * Rec|||1.35<br>[0.03]***|1.43<br>[0.04]***|
|**Underidentification - Weak Identification - W**|**eak Instrume**|**nts Tests**|||
|LM test statistic for underidentification|||84.20|33.38|
|p-value of underidentification LM statistic (And|erson or Kleibe|rgen-Paap)|0|7.58e-09|
|F statistic for weak identification (Cragg-Donald|or Kleibergen|-Paap)|918|813.8|
|Anderson-Rubin chi-sqared test of significance|of endogenous r|egressors|65.43|22.66|
|p-value of Anderson-Rubin chi-sqared test of en|dogenous regre|ssors|0|1.20e-05|

Source: Authors’ calculations based on World Economic Outlook database 2019.

Notes: Robust standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1 Underidentification tests. Ho: matrix of reduced form coefficients has rank=K1-1 -underidentified. Ha: matrix has rank=K1-identified. Weak identification test. Ho: equation is weakly identified. Weak-instrument-robust inference. Tests of joint significance of endogenous regressors B1 in main equation. Ho: B1=0 and overidentifying restrictions are valid.

Table 2 presents the results using a fixed effects estimator (Columns 1 and 2) and an instrumental variable estimator (Columns 3 and 4). During periods of expansion (when approaches zero and E approaches one), changes in output are associated with a more than proportional increase RRr in public consumption in developing economies. In contrast, the same output change leads to a EE less than proportional effect in advanced economies. The semi-procyclical behavior is visible from
international travel; flight information presents in detail the manner in which airlines supply segments of passengers’ international travel.

The information we study, then, is best at documenting the existence of direct flights, and the degree to which flights between specific city-pairs are used. The information we have does not contain information on prices (i.e. ticket fares), nor does it indicate class of service offered, only passenger numbers. Perhaps its most useful attribute is that it indicates whether or not a passenger travelling between two cities has to change planes, which is a key indicator of quality.<sup>9</sup> In focusing our attention on flights, rather than tickets, we seek to complement existing evidence on the effects of air services policy on passenger travel as measured by tickets.<sup>10</sup> The ICAO data is incomplete for years following 2010, so we use passenger data for 2010. Thus all our estimates characterize the situation in 2010. Our counterfactual analysis indicates what would have been the situation in 2010, if the policy scenarios we consider had been in place then. For example, we calculate the predicted air travel patterns if the ACAC were to adopt more liberal policy commitments. The predicted passenger routes are an estimate of what routes would have existed if the proposed policies had been in place in 2010.

**_Policy data_** . Our primary indicator of policy is the Air Liberalization Index (ALI) score assigned to each agreement by an analysis done at the World Trade Organization (WTO).  The WTO created four summary indicators of policy embodied in air services agreements.  These indicators are weighted sums of individual features of the agreements: traffic rights, (lack of) restrictions on capacity, flexibility of pricing allowed, withholding restrictions such as ownership or place of business, designation, and other elements.

> 9 Some very long flights in our database would involve a change in planes. For example, the Chicago, USA to Sydney, Australia flights in the database involve a stopover in Los Angeles, US, and a plane change.  We are not able to distinguish such flights but consider the ICAO indication that there is a flight between two cities to be a close enough proxy for the existence of a direct flight.

> 10 In their study of US data, Cristea et al (2012) find that policy does affect both flights and ticketing demand. Nonetheless they find that much of the increased passenger activity that is attributed to the air services agreement can be linked to the increased number of flights on the initial international segment.

6
the mandatory high school exit exam, SABER 11 (Ferreyra et al., 2021). An HEI must be licensed to open or continue offering a SCP. In addition, HEIs and programs can voluntarily pursue high quality accreditation from the Ministry of Education by complying with the corresponding protocols and requirements (Ferreyra et al., 2021.) Relative to bachelor’s programs, SCPs attract more disadvantaged students—less prepared academically for higher education, with less educated mothers, and more likely to come from lowincome households (Table A1). These disadvantages stress the need to determine whether and how SCPs contribute to students' academic and labor market outcomes.

# **4. Data Sources and Descriptive Statistics**

## **4.1 Data Sources**

**_Pre-higher education student information_** _._ We obtained the SABER 11 dataset from the Ministry of Education’s Colombian Institute for Educational Assessment ( _Instituto Colombiano para la Evaluación de la Educación, ICFES_ ). The dataset includes individual-level SABER 11 exam scores from all students who took the exam between 2000 and 2009 as well as student information reported at the time of the exam, including personal characteristics (gender, age, city where they completed high school) and socioeconomic information (family income and parental education).

**_Student-level higher education exit information_** _._ From ICFES, we also obtained individual-level

test scores of students who took the higher education exit exam, SABER PRO. This exam includes general and subject-specific components.<sup>23</sup> We use data from the reading and quantitative reasoning portions of the general component of the test for the students who took it in the second

> 23 The general component is based on the College Learning Assessment (CLA) and, since 2011, has included five mandatory modules: writing, English, reading/critical thinking, quantitative reasoning, and civic competencies. For a more detailed description of the SABER PRO exam, see Domingue et al. (2017) and Riehl et al. (2020).

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