COVID-19 led to the single largest year-over-year decline in Latin America’s GDP per capita in more than 100 years. Although the region has endured several macroeconomic shocks before, mostly related to financial dislocations, none has been so deep and synchronized. The authors' analysis of the COVID-19 experience for the region and eight economies with available historical data reveals the extent of the damage. Through 2020, four economies suffered “rare disasters” (cumulative contractions by 10 percent or more): Argentina, Mexico, Peru, and Venezuela. Tragically, Venezuela’s macroeconomic collapse matches the largest contraction registered by any country in modern history. In addition, Argentina, Brazil, Mexico, and Venezuela, together with the Latin America regional aggregate, are undergoing “lost decades” (prolonged periods of stagnation), which are unlikely to end soon. While Brazil, Chile, Colombia, and Uruguay did relatively better with COVID-19, they still suffered significant recessions, and their economic performance has lost steam compared with prior decades. Overall, COVID-19 will cast a long shadow in Latin America even as economic growth rebounds. The shock also offers opportunities for a reset, with the appropriate set of macroeconomic policies, advances on microeconomic reforms, and the strengthening of institutions. Whether this set of policies will materialize in the midst of challenging political contexts remains an open question.

Data for 48 countries during the Great Influenza Pandemic imply flu-related deaths in 1918-1920 of 40 million, 2.1 percent of world population, implying 160 million deaths when applied to current population. Regressions with annual information on flu deaths 1918-1920 and war deaths during WWI imply flu-generated economic declines for GDP and consumption in the typical country of 6 and 8 percent, respectively. Higher flu death rates also decreased realized real returns on stocks and, especially, on short-term government bills.

Mortality and economic contraction during the 1918-1920 Great Influenza Epidemic provide plausible upper bounds for outcomes under the coronavirus (COVID-19). Data for 43 countries imply flu-related deaths in 1918-1920 of 39 million, 2.0 percent of world population, implying 150 million deaths when applied to current population. Regressions with annual information on flu deaths 1918-1920 and war deaths during WWI imply flu-generated economic declines for GDP and consumption in the typical country of 6 and 8 percent, respectively. There is also some evidence that higher flu death rates decreased realized real returns on stocks and, especially, on short-term government bills.

relative risk aversion, although LRR makes a moderate contribution. We think the required

We estimate an empirical model of consumption disasters using a new panel data set on personal consumer expenditure for 24 countries and more than 100 years, and study its implications for asset prices. The model allows for permanent and transitory effects of disasters that unfold over multiple years. It also allows the timing of disasters to be correlated across countries. Our estimates imply that the average disaster reaches its trough after 6 years, with a peak-to-trough drop in consumption of about 30%, but that roughly half of this decline is reversed in a subsequent recovery. Uncertainty about consumption growth increases dramatically during disasters. Our estimated model generates a sizable equity premium from disaster risk, but one that is substantially smaller than in models in which disasters are permanent and instantaneous. It yields new predictions for the dynamics of risk-free interest rates, the term structure of interest rates, and the pricing of short-term versus long-term risky assets. The persistence of consumption declines in our model implies that a large value of the intertemporal elasticity of substitution is necessary to explain stock-market crashes at the onset of disasters.

In an 80-country panel since the 1960s, the convergence rate for per capita GDP is around 1.7% per year. This “beta convergence” is conditional on an array of explanatory variables that hold constant countries’ long-run characteristics. The introduction of country fixed effects generates a much higher–and, I argue, misleading–convergence rate. In a much longer time frame–34 countries with GDP data starting between 1870 and 1896–estimation with country fixed effects is more appropriate, and the estimated convergence rate is around 2.4% per year. Combining the point estimates from the post-1960s and post-1870 panels suggests that the conditional convergence rate is between 1.7% and 2.4% per year, an interval that contains the “iron-law” rate of 2%. In the post-1960s panel, estimation without country fixed effects supports the modernization hypothesis, in the form of positive effects of per capita GDP and schooling on democracy and maintenance of law and order. The long-term panel with country fixed effects also supports modernization, in the sense of positive effects of per capita GDP and schooling on the Polity indicator for democracy. A measure of dispersion–the standard deviation of the log of per capita GDP across 25 countries–is reasonably stable since 1870. This lack of “sigma convergence” is consistent with the presence of beta convergence. For 34 countries–including China and India–observed since 1896, the dispersion of per capita GDP declines since the late 1970s, especially when the country data are weighted by population. This sigma convergence reflects particularly the incorporation of China and India into the world market economy. For 29 countries since 1919, the levels and trends in cross-country dispersion are similar for consumption and GDP. Robert J. Barro Department of Economics Littauer Center 218 Harvard University Cambridge, MA 02138 and NBER rbarro@harvard.edu According to the “iron law of convergence,” countries eliminate gaps in levels of real per capita GDP at a rate around 2% per year. Convergence at a 2% rate implies that it takes 35 years for half of an initial gap to vanish and 115 years for 90% to disappear. Convergence-rate parameters are important to pin down because they provide guidance on how fast countries like China and India are likely to catch up to richer countries. The convergence rate may also reveal how fast a poor African country could develop or how rapidly North Korea could catch up to the South, and so on. Empirically, the iron law takes the form of unconditional or absolute convergence in some samples of economies; those that are reasonably homogeneous in terms of long-run or steady-state characteristics. For example, a roughly 2% convergence rate emerged for per capita personal income in a long-term panel of U.S. states in Barro and Sala-i-Martin (1992). This convergence was absolute in the sense of not having to be conditioned on a set of variables that capture differences in long-run positions. The results implied—in accordance with the data— that the U.S. South would not get close in per capita income to the rest of the country for about a century. Applying these results to East versus West Germany suggested that a short time frame for convergence was not a realistic expectation. And, looking forward to the potential I first heard this term applied to my empirical findings on economic growth by Rudi Dornbusch. However, Larry Summers said that Rudi got the term from him. In any event, the term is reminiscent of the “iron law of wages.” According to Wikipedia, this phrase came from Lassalle, but Marx and Engels argued that Lassalle got the idea from Malthus’s theory of population and the terminology from Goethe. Baumol (1986, Figure 2) reported unconditional convergence from 1870 to 1979 for 16 countries (all subsequently OECD members), using data from Maddison (1982). However, De Long (1988) showed that Baumol’s results depended on a sample-selection issue, whereby only countries that were rich toward the end of the sample (1979) were considered. Unconditional convergence did not hold for an expanded sample of 22 countries that were selected based on per capita income in 1870 (De Long [1988, Figure 2]). This sample-selection criticism of Baumol’s (1986) findings was presented earlier by Romer (1986, pp. 1012-1013). Rodrik (2012) finds unconditional convergence in labor productivity across manufacturing industries for recent decades in 118 countries. Barro (2002) found that the predicted slow convergence between East and West Germany accorded with regional data on GDP per worker through the late 1990s. However, wage rates converged faster because of the German government’s transfer and subsidy policies. 2 reunification of North and South Korea, the iron law presents a pessimistic outlook on how rapidly the large gap in per capita product could be eliminated. The 2% convergence rate holds in contexts of conditional convergence for heterogeneous collections of economies that differ substantially in terms of long-run properties. This convergence is conditional in the sense of holding only with an allowance for differences in constant or slowly varying cross-economy characteristics, such as saving rates or fertility rates or quantity of human capital or institutional quality or colonial history or geographical features. For example, a convergence rate around 2% appeared in a cross section of 98 countries in Barro and Sala-i-Martin (1992, Table 3), after conditioning on an array of variables that differed by country. Because of the conditioning variables, these results were more pessimistic than the iron-law convergence rate would suggest. Poor places—for example, many sub-Saharan African countries or North Korea or Burma or Bolivia or Venezuela—might not converge at all if key underlying variables, such as the quality of human capital and institutions, were not improved. The present study uses updated cross-country panels to reexamine the iron law of convergence. One data set comprises a large number of countries with observations for many variables since the 1960s. Another data set exploits recent advances in long-term nationalaccounts information. These data cover over a century but apply to fewer countries and variables. In both contexts, the distinction between absolute and conditional convergence is important. And, within the context of conditional convergence, a key technical issue is whether the cross-country regressions include country fixed effects. 4 In earlier work, Barro (1991) reported conditional convergence for the cross section of 98 countries but did not express the results in terms of a convergence rate. 3 Many analyses of economic growth stress effects from the quality of institutions, gauged particularly by maintenance of the rule of law and democracy. A prominent feature of this analysis is two-way causation between economic development and institutional quality. Specifically, according to the “modernization hypothesis,” economic development spurs the introduction and maintenance of higher quality institutions, including well-functioning representative democracy. The validity of the modernization thesis is important for its own sake—particularly for understanding how democracy evolves—as well as for assessing institutional determinants of economic growth. I use the two updated panel data sets to reassess the empirical status of the modernization hypothesis. From an econometric standpoint, the analysis of modernization turns out to have significant parallels with the study of convergence. Both types of results are sensitive to the treatment of country fixed effects. I. Thoughts on Country Fixed Effects Cross-country empirical findings concerning convergence and modernization are sensitive to the seemingly mundane issue of whether the panel regressions include country fixed effects. The incorporation of these fixed effects into cross-country panel regressions has become almost routine. However, the merits of including these fixed effects are not straightforward, as 5 Knack and Keefer (1995) and Mauro (1995) studied growth effects from rule of law and corruption. Przeworski and Limongi (1993) and Barro (1997, Ch. 2) assessed growth effects from democracy. King and Levine (1993) examined effects of financial institutions on economic growth. Glaeser, La Porta, Lopez-de-Silanes, and Shleifer (2004) argued that institutions should be measured by basic legal constraints on the government, rather than political outcomes, which include official corruption and risk of expropriation. Contributions to the modernization literature include Aristotle (1932), Lipset (1959), Dahl (1991), and Huntington (1991). Marx (1913) extended the modernization idea to a predicted collapse of organized religion under capitalism. This approach applied to economic growth seems to have begun with Knight, Loayza, and Villanueva (1993); Islam (1995); and Caselli, Esquivel, and Lefort (1996). Acemoglu, Johnson, Robinson, and Yared (2005, 2008) advocate the use of country fixed effects in studies of the modernization hypothesis. 4 they involve a tradeoff between two forces, highlighted by Nerlove (2000). The appendix brings out details, using Monte Carlo methods. To fix ideas, consider cross-country panel regressions for the growth rate of per capita GDP. Country fixed effects are attractive as a way to allow for unobserved, persistent country characteristics that influence long-run per capita GDP and are also correlated with observed per capita GDP. That is, rich countries tend to have prospered because they possess persistently favorable characteristics that lead to high steady-state per capita GDP. From this omittedvariables perspective, the exclusion of country fixed effects tends to bias upward the estimated effect of lagged GDP on current GDP and, thereby, bias downward the estimated convergence rate. One example of this effect is the tendency to estimate an absolute convergen

The potential for rare macroeconomic disasters may explain an array of asset-pricing puzzles. Our empirical studies of these extreme events rely on long-term data now covering 28 countries for consumption and 40 for GDP. A baseline model calibrated with observed peak-to-trough disaster sizes accords with the average equity premium with a reasonable coefficient of relative risk aversion. High stock-price volatility can be explained by incorporating time-varying long-run growth rates and disaster probabilities. Business-cycle models with shocks to disaster probability have implications for the cyclical behavior of asset returns and corporate leverage, and international versions may explain the uncovered-interest-parity puzzle. Richer models of disaster dynamics allow for transitions between normalcy and disaster, bring in postcrisis recoveries, and use the full time series on consumption. Potential future research includes applications to long-term economic growth and environmental economics, and the use of stock-index options prices and other variables to gauge time-varying disaster probabilities.

The potential for rare macroeconomic disasters may explain an array of asset-pricing puzzles. Our empirical studies of these extreme events rely on long-term data now covering 28 countries for consumption and 40 for GDP. A baseline model calibrated with observed peak-to-trough disaster sizes accords with the average equity premium with a reasonable coefficient of relative risk aversion. High stock-price volatility can be explained by incorporating time-varying long-run growth rates and disaster probabilities. Business-cycle models with shocks to disaster probability have implications for the cyclical behavior asset returns and corporate leverage, and international versions may explain the uncovered-interest-parity puzzle. Richer models of disaster dynamics allow for transitions between normalcy and disaster, bring in post-crisis recoveries, and use the full time series on consumption. Potential future research includes applications to long-term economic growth and environmental economics and the use of stock-price options and other variables to gauge time-varying disaster probabilities. Robert J. Barro Department of Economics Littauer Center 218 Harvard University Cambridge, MA 02138 and NBER rbarro@harvard.edu José F. Ursua Department of Economics Littauer Center G32 Harvard University Cambridge, MA 02138 jfursua@fas.harvard.edu

Stock-market crashes are informative about the prospects for macroeconomic depressions. Long-term data for 30 countries reveal that, conditional on a crash, the probability of a minor depression is 31 percent and of a major depression is 10 percent. The largest depressions are particularly likely to be accompanied by crashes. We allow for flexible timing between crashes and depressions to compute the covariance between stock-returns and an asset-pricing factor, which depends on the decline of consumption during a depression. With a coefficient of relative risk aversion around 3.5, this covariance accounts for the observed average (levered) equity premium of 7 percent.

We now simulate the Lucas-tree model by viewing the Euler condition in equation 4 as applying to a representative agent at the country level. That is, we neglect the implications of imperfect markets and heterogeneous individuals within countries. However, we also assume that markets are not sufficiently complete internationally for equation 4 to apply to the representative agent in the world. In future work we will assess how the analysis applies to multiple-country regions, rather than country by country. In applying equation 4 to the determination of each country's asset returns, we neglect any implications from international trade in goods and assets; that is, we effectively treat each country as a closed economy. With this perspective, we can view each country-period observation as providing independent information about the relationship between macroeconomic shocks and asset returns. In particular, this independence may be approximately right despite the clear common international dimensions of crises--most obviously from wars but also from financial crises, disease epidemics, and natural resource shocks. We apply the full historical information on disaster probability and sizes to the simulation at each point in time. Thus, we implicitly assume that the underlying parameters are fixed over time and across countries and are known from the outset to the representative agent in each country. We therefore neglect learning about disaster parameters. (35) We focus on the model's implications for the expected rate of return on equity, [r.sup.e], and the risk-free rate, [r.sup.f] and hence for the equity premium. As it stands, the model is inadequate for explaining the volatility of asset prices, including stock prices. For example, the model unrealistically implies a constant price-dividend ratio and a constant risk-free rate. The most promising avenue for extending the model to fit these features--including the high volatility of stock returns--is to allow for shifting uncertainty parameters, notably the disaster probability, p. This possibility is explored in a recent paper by Xavier Gabaix; his results suggest that the extended model can explain volatility patterns without much affecting the implications for expected rates of return, including the equity premium. In a related vein, Ravi Bansal and Amir Yaron have pursued the consequences of shifting expected growth rates, [g.sup.*]. (36) The calibrations of the model follow those in the forthcoming paper by Barro. We set the expected normal growth rate, g, at 0.025; the standard deviation of normal fluctuations, [sigma], at 0.02; and the reciprocal of the intertemporal elasticity of substitution, [theta], at 0.5. (37) These choices of parameters either do not affect the equity premium (g and [theta]) or have a negligible impact ([sigma]). The rate of time preference, [rho], also does not affect the equity premium. However, [rho] (along with g, [sigma], and [theta]) affects levels of rates of return, including the risk-free rate, [r.sup.f] (see equations 6 and 7). Given the lack of useful outside information on [rho], we set [[rho].sup.*] in equation 7 to generate [r.sup.f] = 0.01--roughly the long-run average across countries of real rates of return on bills from table 5. (38) Then P takes on the value needed to satisfy equation 5. The calibrations for the disaster probability, p, and the frequency distribution of disaster sizes, b, use our multicountry study of disaster events. We can then determine the value of [gamma] needed in equation 8 to replicate an unlevered equity premium of around 0.05--the long-run average across countries implied by the data in table 5. Since we always have [r.sup.f] = 0.01, an unlevered equity premium of 0.05 corresponds to an expected rate of return on unlevered equity, [r.sup.e], of 0.06. Table 10 reports results of our simulation for crises gauged by C, and table 11 for those gauged by GDP. …

An earlier study (Barro 2006) applied the Thomas A. Rietz (1988) insight on rare eco? nomic disasters to explain the equity premium and related asset-pricing puzzles. Key param? eters were the probability, p, of disaster and the distribution of disaster sizes, b. In the main analysis, p and the ?-distribution were assumed to be time invariant. An extension to time-vary? ing p is in Xavier Gabaix (2008). Because large macroeconomic disasters are rare, pinning down p and the ?-distribution from historical data requires long time series for many countries, along with the assumption of rough parameter stability over time and across countries. Barro (2006) relied on the long-term international GDP data for 35 countries from Angus Maddison (2003). Using the definition of an economic disaster as a peak-to-trough fall in per capita GDP by at least 15 percent, 60 disas? ters were found, corresponding to p ?* 0.017 per year. The average disaster size was 29 percent, and the empirical size distribution was used to calibrate a model of asset pricing. The underlying asset-pricing theory relates to consumption, C, rather than GDP. This distinc? tion is especially important for wars. For exam? ple, in the United Kingdom during the two world wars, GDP increased while C fell sharply?the difference representing mostly added military spending. Maddison (2003) provides national-accounts information only for GDP. Our initial idea was to add consumption, C, which we measure by personal consumer expenditure because of diffi? culties in separating durables from nondurables in the long-term data. We have not assembled data on government consumption, some of which may substitute for C and, thereby, affect asset pricing. However, this substitution is prob? ably unimportant for military outlays, which are the type of government spending that moves a lot during some disaster events. Maddison (2003) represents a monumental contribution for international studies using long term GDP data. However, although much of the information is sound, close examination revealed many problems. Specifically, Maddison tends to fill in missing data with doubtful assumptions, and this practice is often significant for major crises. As examples, Maddison assumed that Belgium's GDP during WWI and WWII moved with France's; that Mexico's GDP between 1910 and 1920, including the Revolution and Civil War, followed a smooth trend (with no crisis); that GDP for Colombia and Peru over more than a decade moved with the average of Brazil and Chile; and that GDP in Germany for the crucial years 1944-1946 followed a linear trend. There are also some mismatches between original works and published series for GDP in Japan at the end of WWII and Greece during WWII and its Civil War. Given these difficulties, our project expanded to estimating long-term GDP for many countries. The Maddison informa? tion was often usable, but superior estimates can be constructed in many cases. Also, results from recent major long-term national-accounts projects for some countries are now available, including Argentina, Brazil, Chile, Colombia, Greece, Norway, Spain, Sweden, and Taiwan. We are dealing with long-term national accounts data for 41 countries, but the current study applies to the 21 for which we have, thus far, assembled annual data on C and GDP from before WWI to 2006. (See Table 1 for a list of included countries and starting years.) We begin + Discussant: John Campbell, Harvard University.

We build on Angus Maddison’s data by assembling international time series from before 1914 on real per capita personal consumer expenditure, C, and by improving the GDP data. We have full annual data on C for twenty-four countries and GDP for thirty-six. For samples starting at 1870, we apply a peak-to-trough method to isolate economic crises, defined as cumulative declines in C or GDP of at least 10 percent. We find 95 crises for C and 152 for GDP, implying disaster probabilities of 3½ percent a year, with mean size of 21–22 percent and average duration of 3½ years. Simulation of a Lucas-tree model with i.i.d. shocks and Epstein-Zin-Weil preferences accords with the observed average equity premium of around 7 percent on levered equity, using a coefficient of relative risk aversion of 3.5. This result is robust to several perturbations, except for limiting the sample to nonwar crises.

En este trabajo se realiza un diagnostico de la situacion de las finanzas publicas desde las perspectivas macroeconomica y microeconomica. De este analisis se desprenden los principales objetivos que debe perseguir cualquier proyecto de reforma: el incremento de los ingresos publicos y el aumento en la eficiencia del sistema tributario a traves de la eliminacion de diversas distorsiones, en especial las que contiene el Impuesto al Valor Agregado (IVA). Asimismo, se describen las propuestas mas importantes que se han impulsado, asi como los avances que se han logrado en algunos ambitos, por ejemplo, la mejora de la competitividad del sistema tributario via la reduccion de tasas del Impuesto Sobre la Renta (ISR). Por ultimo, se destacan las dificultades que han afrontado las diferentes iniciativas de reforma. Se concluye que la reforma fiscal es un elemento indispensable en la consolidacion de los logros alcanzados en esta materia en los ultimos anos, y una necesidad impostergable frente a las presiones de gasto que deberan enfrentarse en el futuro.