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Wright's adaptive topography describes gene frequency evolution as a maximization of mean fitness in a constant environment. I extended this to a fluctuating environment by unifying theories of stochastic demography and fluctuating selection, assuming small or moderate fluctuations in demographic rates with a stationary distribution, and weak selection among the types. The demography of a large population, composed of haploid genotypes at a single locus or normally distributed phenotypes, can then be approximated as a diffusion process and transformed to produce the dynamics of population size, N, and gene frequency, p, or mean phenotype, 𝑧̄. The expected evolution of p or 𝑧̄ is a product of genetic variability and the gradient of the long-run growth rate of the population, 𝑟̃, with respect to p or 𝑧̄. This shows that the expected evolution maximizes 𝑟̃, the mean Malthusian fitness in the average environment minus half the environmental variance in population growth rate. Thus, 𝑟̃ as a function of p or 𝑧̄ represents an adaptive topography that, despite environmental fluctuations, does not change with time. The haploid model is dominated by environmental stochasticity, so the expected maximization is not realized. Different constraints on quantitative genetic variability, and stabilizing selection in the average environment, allow evolution of the mean phenotype to undergo a stochastic maximization of 𝑟̃. Although the expected evolution maximizes the long-run growth rate of the population, for a genotype or phenotype the long-run growth rate is not a valid measure of fitness in a fluctuating environment. The haploid and quantitative character models both reveal that the expected relative fitness of a type is its Malthusian fitness in the average environment minus the environmental covariance between its growth rate and that of the population.

Our understanding of risk preferences can be sharpened by considering their evolutionary basis. The existing literature has focused on two sources of risk: idiosyncratic risk and aggregate risk. We introduce a new source of risk, heritable risk, in which there is a positive correlation between the fitness of a newborn agent and the fitness of her parent. Heritable risk was plausibly common in our evolutionary past and it leads to a strictly higher growth rate than the other sources of risk. We show that the presence of heritable risk in the evolutionary past may explain the tendency of people to exhibit skewness loving today.

In this paper, following Blanchard and Fischer (1989), I investigate how the presence of the COVID-19 pandemic—the increase in the probability of death—may affect growth and welfare in a scale-invariant R&D-based Schumpeterian model. Without money, the increase in the probability of death has no effect on long-run growth and a negative effect on welfare. By contrast, when money is introduced via the cash-in-advance (CIA) constraint on consumption, the increase in the probability of death decreases long-run growth and welfare under elastic labor supply. Calibration shows that the quantitative effect of an increase in the probability of death on welfare is much larger compared to that on growth.

Forecasts of long-run economic growth are critical inputs into policy decisions being made today on the economy and the environment. Despite its importance, there is a sparse literature on long-run forecasts of economic growth and the uncertainty in such forecasts. This study presents comprehensive probabilistic long-run projections of global and regional per-capita economic growth rates, comparing estimates from an expert survey and a low-frequency econometric approach. Our primary results suggest a median 2010–2100 global growth rate in per-capita gross domestic product of 2.1% per year, with a standard deviation (SD) of 1.1 percentage points, indicating substantially higher uncertainty than is implied in existing forecasts. The larger range of growth rates implies a greater likelihood of extreme climate change outcomes than is currently assumed and has important implications for social insurance programs in the United States.

We develop a new metric for the distribution of educational achievement across countries that can further track the cognitive skill distribution within countries and over time. Cross-country growth regressions generate a close relationship between educational achievement and GDP growth that is remarkably stable across extensive sensitivity analyses of specification, time period, and country samples. In a series of now-common microeconometric approaches for addressing causality, we narrow the range of plausible interpretations of this strong cognitive skills-growth relationship. These alternative estimation approaches, including instrumental variables, difference-in-differences among immigrants on the U.S. labor market, and longitudinal analysis of changes in cognitive skills and in growth rates, leave the stylized fact of a strong impact of cognitive skills unchanged. Moreover, the results indicate that school policy can be an important instrument to spur growth. The shares of basic literates and high performers have independent relationships with growth, the latter being larger in poorer countries.

This research suggests that long-run economic and demographic development in Europe can be better understood when related to long- term trends in gender equality, dating back to the spread of Christianity. We set up a growth model where gaps in female-to-male human capital arise at equilibrium through a coordination process. An economy which over a long stretch of time re-coordinates on continuously more equal equilibria--as one could argue happened in Europe--exhibits growth patterns qualitatively similar to that of Europe.

Business cycles (BCs) may affect entire markets, and significantly alter many firms’ marketing activities and performance. Even though managers cannot prevent BCs from occurring, marketing research over the last 15 years has provided growing evidence that their impact on consumers, and hence on firm and brand performance, depends to a large extent on how firms adjust their marketing mix in response to these macro-economic swings. In this study, we review the growing marketing literature on how to attenuate or amplify the impact of BC fluctuations. Our discussion focuses on three key aspects: (1) the scope of, and insights from, existing BC research in marketing, (2) advancements in the methods to study various BC phenomena in marketing, and (3) some emerging trends that offer new challenges and opportunities for future BC research in marketing.

How did Europe escape the \"Iron Law of Wages?\" We construct a simple Malthusian model with two sectors and multiple steady states, and use it to explain why European per capita incomes and urbanization rates increased during the period 1350-1700. Productivity growth can only explain a small fraction of the rise in output per capita. Population dynamics—changes of the birth and death schedules—were far more important determinants of steady states. We show how a major shock to population can trigger a transition to a new steady state with higher per-capita income. The Black Death was such a shock, raising wages substantially. Because of Engel's Law, demand for urban products increased, and urban centers grew in size. European cities were unhealthy, and rising urbanization pushed up aggregate death rates. This effect was reinforced by diseases spread through war, financed by higher tax revenues. In addition, rising trade also spread diseases. In this way higher wages themselves reduced population pressure. We show in a calibration exercise that our model can account for the sustained rise in European urbanization as well as permanently higher per capita incomes in 1700, without technological change. Wars contributed importantly to the \"Rise of Europe\", even if they had negative short-run effects. We thus trace Europe's precocious rise to economic riches to interactions of the plague shock with the belligerent political environment and the nature of cities.

The intellectual breakthrough contributed by the new growth theory was the recognition that investments in knowledge and human capital endogenously generate economic growth through the spillover of knowledge. However, endogenous growth theory does not explain how or why spillovers occur. This paper presents a model that shows how growth depends on knowledge accumulation and its diffusion through both incumbents and entrepreneurial activities. We claim that entrepreneurs are one missing link in converting knowledge into economically relevant knowledge. Implementing different regression techniques for the Organisation for Economic Co-operation and Development (OECD) countries during 1981 to 2002 provides surprisingly robust evidence that primarily entrepreneurs contributed to growth and that the importance of entrepreneurs increased in the 1990s. A Granger test confirms that causality goes in the direction from entrepreneurs to growth. The results indicate that policies facilitating entrepreneurship are an important tool to enhance knowledge diffusion and promote economic growth.

This paper constructs an original database on physical capital, labor, education, GDP, innovations, technology spillovers, and institutions to analyze the proximate determinants of British economic growth since 1270. Several approaches are taken in the paper to tackle endogeneity. We show that education has been the most important driver of income growth during the period 1270–2010, followed by knowledge stock and fixed capital, while institutions have not been robust determinants of growth. The contribution of education has been equally important before and after the first Industrial Revolution. Overall, the results give strong support to the predictions of Unified Growth Theories.