Advanced economies undergo three transitions during their development: 1. They transition from a rural to an urban economy. 2. They transition from low income growth to high income growth. 3. Their demographics transition from initially high fertility and mortality rates to low modern levels. The timings of these transitions are correlated in the historical development of most advanced economies. I unify complementary theories of the transitions into a nonlinear model of endogenous long run economic and demographic change. The model reproduces the timing and magnitude of the transitions. Because the model captures the interactions between all three transitions, it is able to explain three additional empirical patterns: a declining urban-rural wage gap, a declining rural-urban family size ratio, and most surprisingly, that early urbanization slows development. This third prediction distinguishes the model from other theories of long-run growth, so I test and confirm it in cross-country data.
For a thousand years, income growth was associated with a rising military employment share. But this share peaked in the early 20th century, after which military employment shares fell with income growth. I argue that rising military shares were driven by structural change out of agriculture, and the recent declines are driven by substitution from soldiers towards military goods. I document evidence for this substitution effect: as countries' incomes rise, the ratio of their military expenditure share to their military employment share rises too. I introduce a game theoretic model of growth and warfare that reproduces the time series patterns of military expenditure and employment. The model also correctly predicts the cross-sectional pattern, that military employment and expenditure shares are decreasing in income during wars. Finally, I show that faster economic growth can reduce military expenditure in the long run.
We demonstrate that a simple asset market restriction is sufficient to resolve the Backus-Smith puzzle, that relative consumption and real exchange rates are negatively correlated. We argue that prior attempts to use incomplete asset markets to resolve the puzzle employed over-simplified asset structures or other assumptions so that the models could be solved with perturbation methods. We introduce a simple international macro model to show that if a portfolio choice includes foreign and domestic non-contingent bonds, then the portfolio optimality conditions imply that the Backus-Smith puzzle will hold for a large set of reasonable calibrations. We show how standard perturbation methods are poorly suited to accurately solve our model, so we employ a novel global solution method that generalizes the approach of Maliar and Maliar (2015) to solve a wide class of models. We make three further contributions: the model generates home bias of bond holdings; it produces failure of uncovered interest rate parity; and we illustrate that global solution methods quickly and accurately solve models where local perturbation methods fail.
This paper presents a general solution method for rational expectations models with dispersed information when the information process is endogenous. First, I show how to solve models with exogenous information by applying a single matrix equation. Next, I present an algorithm, Signal Operator Iteration, which solves the model when information is endogenous. I characterize conditions under which the solution is unique and the algorithm converges. Finally, I apply the solution method to a model of local information. Firms observe prices and quantities in their own market, but not the aggregate state of the economy. They must make inferences about aggregate shocks through the impacts on endogenous prices. In this model, money is non-neutral and firms exhibit hump-shaped impulse response functions.
The share of aggregate income paid as compensation to labor is frequently used as a proxy for income inequality. If capital holdings are very concentrated among high income individuals, increasing their share of GDP, all else equal, widens the gap with poorer workers. Indeed, two striking features over the last three decades of many advanced and developing economies are the declining labor shares in income and the rise in income inequality. The relationship between factor shares and inequality, however, is not so simple in a richer world with realistic features such as endogenous home decisions and capital-skill complementarity. In such a world, total inequality will change with (i) the labor share, (ii) the amount of within-labor and within-capital income inequality, and (iii) the degree to which the highest wage earners are also those earning the highest capital incomes. Macroeconomic trends and shocks that impact any one of these three moments are likely to impact simultaneously all of them. We develop a framework where all these terms are jointly determined and estimate the model to clarify the roles of changing technology, policies, and factor proportions on labor shares and total income inequality around the globe.
Why is growth slowing? Two facts are documented: 1. Richer countries spend a greater share of their income on research and development, and 2. Countries with high spending on research and development grow slower. These facts are evident in both the US time series and in the cross-section of countries. The paper proposes a model that explains these two facts, driven by declining returns to research and development. As technology advances, it costs a greater share of output to increase at the same rate; innovators compensate by spending more in R&D, but cannot compensate fully. In the long run, the R&D share of output asymptotes to 3.0-3.9%, and the per capita GDP growth rate declines to 1.0-1.5%.