rafmacalaba/datause-encoder-data huggingface dataset:
19 6A cursory inspection of the data in fact dictates that the cyclical pattern of spreads over time are related to some global- and macroeconomic events such as the oil shocks and industrialized counrry growth rates. These two variables are also correlated with the number of banks that entered the Eurocurrency market. Hence a more sophisticated approach would require a model employing such variables to explain the spread behavior over time. Since this is beyond the purpose of this study, we implemented this simpler approach.

7The perfect competition assumption is not necessary for the empirical model derived. A very similar model is developed under the monopolistic competitioi assumption. See Feder and Just (1977).

8Even though this form is not subject to the problem of scaling it is subject to that of translation which means it is sensitive to changes of the origin for X.

9This particular set of variables was employed for direct comparibility to existing studies on credit terms (see Edwards (1984)). Similar variables have also been employed in the empirical literature as determinants of rescheduling probabilities (see Eaton and Taylor (1986) and McDonald (1982) for a review. In creating the ratios in this study, we have employed monthly data where available.

10We have presented the estimations for only one of these specifications. Others are quite similar to the one presented and are available from the author upon request.

11One may suspect that OLS estimates of this relationship may be inconsistent. X and w of equation (4) may be correlated if the borrower's choice of X in part depends on the spread. This, however, is not likely. It is important to recall that most measures of the experience
Estimated Equation for **XSB** XSB 377.7 - 102.5 Ql - 166.3 Q2 - 142.8 Q3 + .3496 XSB(T-4) (74.96) (20.90) (17.05) (12.21) (.1195) - 13.55 PSX - 13.18 EXR - 8.892 NONUSS (3.313) (47.30) (4.258) R2 .838, _72_ - .816, DW = 2.07, ly - 32.58, Data - 1973:1 - 1987:4 Estimated Equation for CRUSH CRUSH - 132.1 - 62.37 (1 - 72.25 Q2 - 30.66 Q3 + .4891 CRUSH(T-1) (142.4) (14.78) ( 38.38) (36.82) (.1823) + .01582 COF + .004419 PIGOF - .0001748 BROF - 18.31 RPAFS (.005544) (.002090) (.0001437) (5.665) + 19.60 RPYD (59.67) R<sup>2</sup> = .910, _T2_ _ .894, Drw - 1.75, cy - 25.25, Data - 1973:1 - 1987:4 Estimated Equation for RPAFS RPAFS - 5.833 - 2.029 Q1 - 1.658 Q2 - 2.741 Q3 + .2257 RPAFS(T-1) (3.563) (.7850) (1.184) (1.664) (.1101) **_+_** .0004466 COF + .2247 PIGOF - .000006121 BROF - .1134 RRS (.0001898) (.00007176) (.000002598) (.09747) - .09715 NONUSS - .003688 KPRISBE (.1467) (.001298) R<sup>2</sup> = .863, K<sup>2</sup> = .835, DW = 1.98, ay = 1.128, Data = 1973:1 - 1987:4

# **Quarterlv Meat Supp1v** Block

The structure of the meat supply block follows the earlier generic discussion with breeding herd, numbers on feed, production, and import/export equations included for cattle, hogs, and poultry. The beef supply component of the meat supply block includes the following estimated equations.

Estimated Equation for CCOWKE CCOWKE = -555.4 + 769.0 Q1 + 749.4 Q2 + 13.78 Q3 - 101.4 RPCPB (372.3) (193.5) (193.2) (193.3) (24470.) - 55.94 RRS + 68.37 RRS(T-1) (62.41) (59.72)
the model and its predictions. The Case Study: Evidence for India section contains the calibration exercise and results. The Financial Development, Permanent Income Shock, and Relative Consumption Volatility in a Small Open Economy section presents the implications in a small open economy setup. The final section concludes.

# CONSUMPTION VOLATILITY AND FINANCIAL DEVELOPMENT

Recent empirical evidence on emerging economy business cycles shows an increase in the volatility of consumption relative to that of output after financial sector reform in Asia, Turkey, and India (Kim et al. 2003; Alp et al. 2012; Ghate et al. 2013). The relative volatility of consumption in the pre- and post-financial sector reform period for some developing countries are estimated (table 1). The choice of the date on which reform took place is based on Kim et al. (2003), Singh et al. (2005), Rodrik (2008), Alp et al. (2012), and Aslund (2012). The analysis is based on annual data for a set of emerging economies.<sup>1</sup> The volatility of consumption relative to that of output in these countries, in the pre- and postreform period, shows that many emerging economies exhibit similar behaviour in that relative consumption volatility increases after reform (table 1).

Financial development has been a major component of reform. A commonly used indicator of financial development, namely, total bank deposits to GDP ratio, for a set of emerging economies, on average, shows a rise in the indicator over time (figure 1). The rising trend in the ratio is also visible for individual countries (figure 1).

The indicators on financial depth, depicted by the density of commercial bank branches and depositors with commercial banks in emerging economies, in the beginning and in the end of the last decade, indicate an increase in access of

> 1 The span of the analysis varies across countries given the availability of the data. Table S1.1 in the Supplemental Appendix S1, lists period of analysis for each country. The reform date for each region, and the sources of the documentations indicating the reform dates are also reported in this table.

5
-2-

the legItImac- of privnte ownership o! lard. Incomplete nationalizatlon of land In Eastern and Central Europe appears markedly to have altered the political economy of agricultural reform, and weakened the constituency of support for the Inherited system.

In the USSR, private ownership of land Is at this writing not yet legal at the Unlon level, despite recent legislation that legalized private ownership of other assets. Republics are proceeding with their own land laws that recognize different forms of Individual tenure with varying restrictions on transferability. Although It Is difficult to predict the future course of policies, It appears le3s liKely that fully functioning land markets will develop In the USSR In the near term than In Eastern Europe. The state will retain ownership of most If not all agricultural land, but will allow a more diverse set of users to have contractual access to the land. The parties Involved In contractual agreements will be the state and collective farms, local councils, Individuals, and small cooperatives.

Under the new tenurlal arrangements, those who farm land are to pay for the use of It. With land markets constrained or Inactive, land use fees must be set administratively. There Is no consensus In the Soviet economics literature yet on how best to value land administratively. The Union level land law of March, 1990 mandates a full scale land cadastre to record characteristics of land. Reliance on cadastral results would greatly postpone the Introduction of land use fees. Furthermore, there Is no clear methodology for transforming cadastral surveys Into land values.

In a well functioning competitive market economy, agricultural land would earn Its marginal value product In agricultural production. This value can be measured empirically from production data and actual or proposed prices. The marginal value product will depend on the structure of output prices, the productlon technology, and managerial efficiency at the farm level. Valuation of land Is Intimately llnked to the
2003). Knodel and co-authors have several studies on the elderly in Cambodia and Thailand; there is much less evidence for Sub-Saharan Africa. The most rigorous sample survey-based evidence arguably comes from South Africa (see, for example, studies in Cohen and Menken 2006).<sup>4</sup> Yet, the combination of the old-age pension scheme which provides cash transfer to older adults and the very severe HIV epidemic suggest that the impacts observed in South Africa may be quite different than impacts in other African countries (Hosegood and Timaeus, 2006).

Moreover, most of these studies focus on demographic impacts (living arrangements, population age/gender structure) rather than more direct measures of economic impacts. A second problem is that many studies in this literature tend to have small, often specially selected samples and be case-based; see, for example, Agyarko (2002) and Ogunmefun (2007). These studies lack discussion of the problems of endogeneity in both living arrangements and mortality events (i.e. deaths do not randomly occur in this context). The existing evidence is usually not longitudinal in nature, thus prohibiting an understanding of “the full impact of HIV/AIDS...assessed over time” (Naidu and Harris, 2005). It is often presumed that studies may understate impacts if households use coping strategies, such as assistance from neighbors or selling off assets, which may mitigate direct impacts on well-being, at least in the short-run (World Bank, 1997). Long-run impacts may differ from evidence drawn from short-run panel data (see, for example, Carter _et al_ ., 2007, who explore three rounds of a 12-year household panel in South Africa). Furthermore, as noted above, there may be specific gender dimensions (with respect to gender of deceased and gender of survivors) which warrant further study.

The objective of this study is to provide empirical evidence of the impacts of adult deaths on older adults using long-run panel data from Kagera, a region of northwest Tanzania. Using a longitudinal data set covering 13 years, we analyze a sample of individuals who are 50 or older in 2004. The time span of the data allows us to assess long-run impacts of adult death, with particular attention paid to gender dimensions of the surviving older adult and the deceased. We focus on several outcomes. We explore how

> 4 Although not focusing specifically on the elderly, in the journal _AIDS_ November 2007 volume 21 supplement 7 on “Poverty, HIV and AIDS: Vulnerability and Impact in Southern Africa” 7 of 10 papers are on South Africa, 1 on Zimbabwe, and 2 are cross-country studies.

4
was a multi-purpose survey of conditions, practices,<sup>outcomes, and costs of primary</sup> schooling.

Design and Sample 32. The sampling design for the survey involved a multistage<sup>cluster sample with</sup> probability of selection proportional to size within<sup>the first two stages. There are 12</sup> educational regions in Thailand, plus the Bangkok<sup>metropolitan area. Within each region,</sup> there are provinces (n=72); within provinces, there<sup>are districts and within districts there</sup> are schools.

33. The first stage of sampling involved a stratified random<sup>sample of 25% (n= 18) of the</sup> provinces within strata constituted by educational<sup>regions. Within provinces, 20% of the</sup> districts were sampled at random and, within districts,<sup>30% of the schools were sampled.</sup> Within each school every principal was administered<sup>the principal questionnaire. Moreover,</sup> within each school, every sixth grade teacher was selected;<sup>and one additional teacher from</sup> each other grade was sampled at random. Each teacher<sup>was administered the teacher</sup> questionnaire.

34. Finally, within schools, one sixth grade class was selected<sup>at random, although many</sup> schools contain only one sixth grade class. Within each<sup>class, all students were administered</sup> achievement tests in the **five** areas of the 1978 curriculum<sup>(Thai language, mathematics, life</sup> 13
Dessus, S. and A. Varoudakis (2013). “Protecting Public Investment against Shocks in the West African Economic and Monetary Union.” World Bank Policy Research Working Paper #6562 (August).

- Dissou, Y. and S. Didic (2013) Public Investment and Economic Growth: A Dynamic General Equilibrium Analysis with Heterogeneous Agents, Mimeo, Department of economics, University of Ottawa, Ottawa, Canada.

- Dissou, Y. and L. Karnizova (2012). “Emission Cap or Emission Tax? A Multi-sector Business Cycle Analysis.” Working paper #1210E, Department of Economics, University of Ottawa, Canada.

- Fair, R.C. and J.B. (1983) "Taylor. Solution and maximum likelihood estimation of dynamic nonlinear rational expectations models" _Econometrica_ , 51:1169-1185.

- Gagnon, J. E. (1990).Solving the stochastic growth model by deterministic extended path. _Journal of Business & Economic Statistics_ , _8_ , 35-36.

- Gelb, A. et al. (1988). Oil Windfalls: Blessing or Curse?” Oxford University Press for the World Bank, New York.

- Go, D., S.Robinson, K. Thierfelder, and R. Utz.(2013). “Dutch Disease and Spending Strategies in a Resource-Rich Low-Income Country – the Case of Niger.” World Bank Policy Research Working Paper #6691 (November).

- Hayashi, F. (1982). Tobin’s marginal q and average q: A neoclassical interpretation, _Econometrica 50_ , 213-224.

- Heer, B., & Maußner, A. (2008). Computation of business cycle models: a comparison of numerical methods. _Macroeconomic Dynamics_ , _12_ , 641-663.

- Love, D. R. F. (2010) "Revisiting deterministic extended-path: a simple and accurate solution method for macroeconomic models", International Journal of Computational Economics and Econometrics, 1(3/4) 2010

- Medina, J. P. & C. Soto (2005), Oil Shocks and Monetary Policy in an Estimated DSGE Model for a Small Open Economy, Working papers, Central bank of Chili.

- Mehlum, H., K. Moene, and R. Torvi (2006). “Insitutions and the Resource Curse.” Economic Journal, Vol. 116, No. 508, pp. 1-20.

- Melina, G., S. S. Yang, and L. Zanna (2014). “Debt Sustainability, Public Investment, and Natural Resources in Developing Countries: the DIGNAR Model.” IMF Working Paper 14/50 , Washington, International Monetary Fund.

- Ogaki, M., Ostry, J., Reinhart, C. (1996). Saving Behavior in Low- and Middle-income  Developing Countries: A Comparison. IMF Staff Papers 43 (1), 38–71.

- Pritchett, Lant, 2000. "The Tyranny of Concepts: CUDIE (Cumulated, Depreciated, Investment Effort) Is Not Capital," _Journal of Economic Growth_ , Springer, vol. 5(4), pages 361-84, December.

- Sachs, J. and A. Warner (1997). “Natural Resource Abundance and Economic Growth.” In G. Meier and J. Rauch, eds. Leading Issues in Economic Development. , Oxford, Oxford University Press.

- Schmitt-Grohé, S. and M. Uribe (2003) Closing small open economy models, Journal of International Economics 61 (2003), pp. 163–185.

- Shea, J. (1995). “Union Contracts and the Life-Cycle/Permanent Income Hypthesis.” _American Economic Review_ 85(March):186-200.

31
Carrying out the simulations involves the recursive solution to the system of non-linear equations (3), (7), (12), (14), and (15) with seven endogenous variables ( _x_<sup>_l_</sup> _t_<sup>_, x_</sup> _t_<sup>_k, xe_</sup> _t_<sup>_, x_</sup> _t_<sup>_m, γl, γe,_and</sup><sup>_γm_).Simulations are run in the General Al-</sup> gebraic Modeling System (GAMS), a high-level modeling system for mathematical programming problems, employing the non-linear equation solver CONOPT (Drud 1996).

# **5.1 Petrochemical Industry**

Figures 3 and 4 illustrate simulation results for the U.K. petrochemical industry. Both figures show percentage changes in capital, labor, energy, and materials inputs over time.<sup>32</sup> These percentage changes are relative to the base year 2005, at which time we assume that all factor inputs are in steady-state equilibrium.

<!-- Start of picture text --> 10.00%<br>Materials<br>5.00% Labor<br>0.00%<br>Capital<br>Energy<br>-5.00%<br>-10.00%<br>-15.00%<br>2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br><!-- End of picture text --> Figure 3: Effect of $ 30 Carbon Tax on Energy Consumption in the U.K. Petrochemical Industry (Assuming no Price Induced Investment Response) Figure 3 shows the effect of an unanticipated 17 percent increase in the energy input price, assuming no investment response to energy prices (e.g., _φ_<sup>_e_</sup> = 0). Under this assumption changes in energy efficiency in capital stock

> 32Figures 3 and 4 show somewhat erratic fluctuations along the optimal time paths for capital, labor, energy, and materials inputs. These small fluctuations reflect optimization errors of a non-linear solver and should be ignored.

26
# **Online Appendix**

## **A Data Appendix**

In this section, we list and describe the multiple data sources we use in this paper, as well as the necessary data cleaning and adjustment procedures we perform. Where relevant, we show descriptive statistics based on the data. We cover not only the data sources mentioned in Section III, but also other ancillary data sources.

### **A.A Trade Policy**

We obtained Sri Lanka’s Extraordinary Gazettes on Imports and Exports (Control Regulations) from March 2020 to October 2022, which allow us to identify the HS8 products that were subject to import bans.<sup>95</sup> We digitized the gazettes and manually inspected all entries to create a database with HS8 products and start and end dates of import bans. Appendix Figure A1 shows the timing of the fertilizer import bans, while Appendix Table A1 shows the list of HS8 product codes corresponding to fertilizers subject to the import ban.

Figure A1: Timing of Fertilizer Import Bans <!-- Start of picture text --> Jan/2017 Jan/2018 Jan/2019 Jan/2020 Jan/2021 Jan/2022<br>Month<br>.6<br>.4<br>.2<br>Fraction of fertilizer products banned<br>0<br><!-- End of picture text --> _Notes_ : For each month between January 2017 and September 2022, the chart shows the fraction of HS8 fertilizer products that were subject to an import ban in that month. The denominator of the fraction is 25, which is the number of fertilizer products that were imported by Sri Lanka at any point between 2017 and 2022. A fertilizer product is defined as any HS8 product that is listed in Chapter 31 of the HS system. The data comes from Sri Lanka’s Extraordinary Gazettes.

> 95The Extraordinary Gazettes were accessed at: http://www.imexport.gov.lk/index.php/en/downloads/gazette.html

56
Overall, the results presented in this section lend support to the efficiency focus among finance training recipients and the growth focus among marketing training recipients.

# **5.4. Which Business Training and for Whom?**

The analysis next presents statistical tests for Hypotheses 3 and 4 developed in Section 2. Specifically, we test whether the growth focus of marketing training is more valuable for firms with narrow exposure, and whether the efficiency focus of finance training is more valuable for larger, more established firms. Business exposure and establishment are composite variables that were constructed based on questions in the baseline survey. The full set of these questions and their summary statistics are reported in Table 1 and discussed in Section 4.1.

Table 11 presents the regression results. Columns (1) and (2) present heterogeneous treatment effects based on business establishment, and Columns (3) and (4) present results based on business exposure. The results show that the finance training did not improve business profits for firms with a below median score on the composite measure of business establishment. However, in contrast, the interaction term is strongly positive and statistically significant, showing that businesses with above median scores benefited significantly from the finance training. In terms of magnitude, the treatment effect for more established firms is equivalent to a 68% increase in business profits over the control group or a 0.35 standard deviation improvement.

In line with an efficiency focus explanation, these results show that small firm owners who have been running more established businesses prior to training tend to achieve greater profit gains when they receive the finance and accounting training program. Building finance skills is particularly helpful for firms who have reached a minimum threshold in terms of scale, and so the finance and accounting skills developed by the owner can actually be put into practice to reduce costs and increase efficiencies in the business, thereby increasing profits and improving bottom line performance.

In terms of business exposure, Column (4) of Table 11 shows that firms with narrow exposure benefit disproportionately more than those who are already highly exposed at baseline. Specifically, the treatment effect for firms with narrow exposure represents a 123% increase in 28
# **Figure 10 Fiscal expenditure and SWFs in Australia and Norway**

<!-- Start of picture text --> A. Australia B. Norway<br>Percent Fiscal expenditure Index Percent Fiscal expenditure $/bbl<br>SWF SWF 120<br>50 Commodity export price (RHS) 140 300 Oil price (RHS) 100<br>120 250<br>40<br>80<br>100 200<br>30 80 60<br>150<br>20 60 100 40<br>40<br>10 20 50 20<br>0 0 0 0<br>2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021<br><!-- End of picture text --> _Sources_ : Future Fund (website); International Monetary Fund; Norges Bank; World Bank. _Note_ : bbl = billion barrels; SWF = sovereign wealth fund.

A. B. Fiscal expenditure and assets under management of SWFs are expressed as percentages of GDP.

40
After the East Asian Financial Crisis in 1997/8, firms which had not implemented mandatory retirement started to do so as a way of slowing wage increases associated with seniority-based wage systems (Cho and Kim, 2005).

In Indonesia, government employees and civil servants face mandatory retirement at 55, and this age is followed by some large private employers as well (Brodjonegoro and Simanjuntak, 2002; Leechor, 1996). From 1995, the “normal retirement age” was considered to be 55 with a maximum age of 60, with these retirement ages applying to larger private sector employers as well as the government.<sup>15</sup> Apart from the “normal retirement age,” however, there are numerous exceptions made through presidential and ministerial decrees, that raise the retirement ages for some occupations. Doctors and other high skilled professional civil servants may retire at 60, more senior levels of civil service are able to retire as late as 65 and university professors face mandatory retirement at age 70. Employees of smaller scale enterprises and the self-employed, who comprise the urban informal sector, do not face mandatory retirement.

The higher employment rates of older urban men and women in Indonesia and Korea (Figure 2) suggest that mandatory retirement from some occupations and types of employers does not mechanically lead to permanent exit from productive employment. Existing research on older workers in both countries suggests that an impending retirement creates incentives for forwardlooking workers to leave employers preemptively, either to start their own businesses or to start second careers working for smaller private sector employers.<sup>16</sup> One significant difference across workers in urban and rural areas of China, Indonesia and Korea lies in the share of the retirement age workforce with access to pensions. In China, evidence from China Health and Retirement Longitudinal Study (CHARLS) pilot suggests that, of urban residents over age 60, 79 and 54 percent of men and women, respectively, have access to pension

> 15Government Regulation No 32 (1979) specifies 55 as the retirement age for civil servants and became the benchmark for the “normal retirement age” followed in the private sector as well. Ministry of Labor Regulation No 2 (1995) stipulates that the normal retirement age is 55 and the maximum is 60, and these are also the ages at which eligible retirees are able to start collecting pensions.

> 16McKee (2006) finds that in Indonesia, half of government workers move into either the private sector or into selfemployment, and 61 percent of workers who leave their private sector jobs move into self-employment. In Korea, self-employment was one response to lay-offs from larger employers in the wake of the 1997/8 financial crisis (Sohn, 2007), and continues to be an important source of employment for older males (Lee 2009). Lee and Lee (2011) note differences in the retirement ages of self-employed and wage-salary earners, but do not discuss the incentive to move into self-employment ahead of mandatory retirement among wage and salary earners who wish to continue working.

9