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This paper argues that, in the presence of intersectoral input—output linkages, microeconomic idiosyncratic shocks may lead to aggregate fluctuations. We show that, as the economy becomes more disaggregated, the rate at which aggregate volatility decays is determined by the structure of the network capturing such linkages. Our main results provide a characterization of this relationship in terms of the importance of different sectors as suppliers to their immediate customers, as well as their role as indirect suppliers to chains of downstream sectors. Such higher-order interconnections capture the possibility of \"cascade effects\" whereby productivity shocks to a sector propagate not only to its immediate downstream customers, but also to the rest of the economy. Our results highlight that sizable aggregate volatility is obtained from sectoral idiosyncratic shocks only if there exists significant asymmetry in the roles that sectors play as suppliers to others, and that the \"sparseness\" of the input—output matrix is unrelated to the nature of aggregate fluctuations.

A modern economy is an intricately linked web of specialized production units, each relying on the flow of inputs from their suppliers to produce their own output which, in turn, is routed towards other downstream units. In this essay, I argue that this network perspective on production linkages can offer novel insights on how local shocks occurring along this production network can propagate across the economy and give rise to aggregate fluctuations. First, I discuss how production networks can be mapped to a standard general equilibrium setup. In particular, through a series of stylized examples, I demonstrate how the propagation of sectoral shocks—and hence aggregate volatility— depends on different arrangements of production, that is, on different “shapes” of the underlying production network. Next I explore, from a network perspective, the empirical properties of a large-scale production network as given by detailed US input-output data. Finally I address how theory and data on production networks can be usefully combined to shed light on comovement and aggregate fluctuations.

Steel slag is a main form of solid waste. Using this component to replace part of the aggregate in an asphalt mixture is an effectively way of treating solid waste. To study the performance degradation of asphalt mixture with various content of steel slag under heavy loading, some large-sized basalt hot mixed asphalt mixture (BHMA) and steel slag hot mixed asphalt mixture (SHMA) in a form of specimens were prepared and a heavy loading wheel tracking test was conducted. The aggregate characteristics of basalt and steel slag were measured. The deformation and skid resistance of the asphalt mixture with different content of steel slag was tested and analyzed. Due to the particle characteristics of steel slag aggregate, it was found that a low content of steel slag can effectively improve the resistance to deformation and skid resistance of the asphalt mixture under heavy loading. The response of SHMA can still meet the pavement technical requirement after long-term heavy loading service. The main change in the mixture under heavy loading is the crushing of the 9.5–16 mm aggregate, and the content of this part also significantly affects the deformation. This study explains the mechanism of degradation of SHMA under heavy loading: the large aggregate is crushed and forms a new aggregate skeleton structure.

Newly developed historical time series on public debt, along with data on external debts, allow a deeper analysis of the debt cycles underlying serial debt and banking crises. We test three related hypotheses at both \"world\" aggregate levels and on an individual country basis. First, external debt surges are an antecedent to banking crises. Second, banking crises (domestic and those in financial centers) often precede or accompany sovereign debt crises; we find they help predict them. Third, public borrowing surges ahead of external sovereign default, as governments have \"hidden domestic debts\" that exceed the better documented levels of external debt.

We develop a model that, at the aggregate level, is similar to the one-sector neoclassical growth model; at the disaggregate level, it has implications for the path of observable measures of technology adoption. We estimate it using data on the diffusion of 15 technologies in 166 countries over the last two centuries. Our results reveal that, on average, countries have adopted technologies 45 years after their invention. There is substantial variation across technologies and countries. Newer technologies have been adopted faster than old ones. The cross-country variation in the adoption of technologies accounts for at least 25 percent of per capita income differences.

We show that \"commodity currency\" exchange rates have surprisingly robust power in predicting global commodity prices, both in-sample and out-of-sample, and against a variety of alternative benchmarks. This result is of particular interest to policy makers, given the lack of deep forward markets in many individual commodities, and broad aggregate commodity indices in particular. We also explore the reverse relationship (commodity prices forecasting exchange rates) but find it to be notably less robust. We offer a theoretical resolution, based on the fact that exchange rates are strongly forward-looking, whereas commodity price fluctuations are typically more sensitive to short-term demand imbalances.

Much of the analysis of economic growth has focused on the study of aggregate output. Here, we deviate from this tradition and look instead at the structure of output embodied in the network connecting countries to the products that they export. We characterize this network using four structural features: the negative relationship between the diversification of a country and the average ubiquity of its exports, and the non-normal distributions for product ubiquity, country diversification and product co-export. We model the structure of the network by assuming that products require a large number of non-tradable inputs, or capabilities, and that countries differ in the completeness of the set of capabilities they have. We solve the model assuming that the probability that a country has a capability and that a product requires a capability are constant and calibrate it to the data to find that it accounts well for all of the network features except for the heterogeneity in the distribution of country diversification. In the light of the model, this is evidence of a large heterogeneity in the distribution of capabilities across countries. Finally, we show that the model implies that the increase in diversification that is expected from the accumulation of a small number of capabilities is small for countries that have a few of them and large for those with many. This implies that the forces that help drive divergence in product diversity increase with the complexity of the global economy when capabilities travel poorly.

Health and income are strongly correlated both within and across countries, yet the extent to which improvements in income have a causal effect on health status remains controversial. We investigate whether short-term fluctuations in aggregate income affect infant mortality using an unusually large data set of 1.7 million births in 59 developing countries. We show a large, negative association between per capita GDP and infant mortality. Female infant mortality is more sensitive than male infant mortality to negative economic shocks, suggesting that policies that protect the health status of female infants may be especially important during economic downturns.

This paper presents a simple new method for measuring \"wealth effects\" on aggregate consumption. The method exploits the stickiness of consumption growth (sometimes interpreted as reflecting consumption \"habits\") to distinguish between immediate and eventual wealth effects. In U.S. data, we estimate that the immediate (next quarter) marginal propensity to consume from a $1 change in housing wealth is about 2 cents, with a final eventual effect around 9 cents, substantially larger than the effect of shocks to financial wealth. We argue that our method is preferable to cointegration-based approaches, because neither theory nor evidence supports faith in the existence of a stable cointegrating vector.

The phenomenon of paid search advertising has now become the most predominant form of online advertising in the marketing world. However, we have little understanding of the impact of search engine advertising on consumers' responses in the presence of organic listings of the same firms. In this paper, we model and estimate the interrelationship between organic search listings and paid search advertisements. We use a unique panel data set based on aggregate consumer response to several hundred keywords over a three-month period collected from a major nationwide retailer store chain that advertises on Google. In particular, we focus on understanding whether the presence of organic listings on a search engine is associated with a positive, a negative, or no effect on the click-through rates of paid search advertisements, and vice versa for a given firm. We first build an integrated model to estimate the relationship between different metrics such as search volume, click-through rates, conversion rates, cost per click, and keyword ranks. A hierarchical Bayesian modeling framework is used and the model is estimated using Markov chain Monte Carlo methods. Our empirical findings suggest that click-throughs on organic listings have a positive interdependence with click-throughs on paid listings, and vice versa. We also find that this positive interdependence is asymmetric such that the impact of organic clicks on increases in utility from paid clicks is 3.5 times stronger than the impact of paid clicks on increases in utility from organic clicks. Using counterfactual experiments, we show that on an average this positive interdependence leads to an increase in expected profits for the firm ranging from 4.2% to 6.15% when compared to profits in the absence of this interdependence. To further validate our empirical results, we also conduct and present the results from a controlled field experiment. This experiment shows that total click-through rates, conversions rates, and revenues in the presence of both paid and organic search listings are significantly higher than those in the absence of paid search advertisements. The results predicted by the econometric model are also corroborated in this field experiment, which suggests a causal interpretation to the positive interdependence between paid and organic search listings. Given the increased spending on search engine-based advertising, our analysis provides critical insights to managers in both traditional and Internet firms.