What is the economic rationale for investing in science? Based on an open economy model of creative destruction, we characterize four key factors of optimal investment in basic research: the stage of economic development, the strength of the manufacturing base, the degree of openness, and the share of foreign‐owned firms. For each of these factors, we analyze its bearings on optimal basic research investment. We then show that the predicted effects are consistent with patterns observed in the data and discuss how the factor‐based approach might inform basic research policies.
The literature extensively discusses the increasing commitment toward comprehensive structural reform of China’s economy as it targets to achieve high quality and sustainable economic growth. This research investigates the inherent relationship between supply-side structural reform (SSSR) and dynamic capital structure adjustment in Chinese-listed firms. Our results show that SSSR’s introduction has significantly improved the adjustment speed toward the optimal debt ratio, especially for firms with high indebtedness and low investment performance. Importantly, China’s bond market plays a crucial role through SSSR for firms’ debt ratio to adjust toward their optimal level. However, there is no such evidence among state-owned enterprises (SOEs), suggesting that the structural reform concerning corporate capital structure for SOEs is more challenging and longstanding when compared with non-SOEs.
This research constructs a simple dynamic model to illustrate the micro‐mechanism of industrial upgrading along the global value chains. Our model predicts that as firms move up from downstream to upstream stages, (a) there is higher profitability if and only if the following three conditions are satisfied. First, the increasing rate of sunk cost (including R&D expenditure) over sequential stages of production cannot be sufficiently large (endogenous sunk cost effect). Second, the decreasing rate of change of intermediate input demand with respect to the price set by firms at a production stage cannot be sufficiently high (intermediate input price effect). Third, the decreasing rate of change of intermediate input demand with respect to the pricing dynamics over the sequential stages of production cannot be sufficiently large (sequential pricing uncertainty effect); (b) total cost is lower if and only if the decreasing rate of change of input demand with respect to the price is sufficiently large; (c) output is higher if and only if and the decreasing rate of change of input demand with respect to the price is not sufficiently large; and (d) the price decreases. We show that the empirical patterns revealed in China are consistent with our model's predictions.
We describe a problem in complex networks we call the Node Vector Distance (NVD) problem, and we survey algorithms currently able to address it. Complex networks are a useful tool to map a non-trivial set of relationships among connected entities, or nodes. An agent—e.g., a disease—can occupy multiple nodes at the same time and can spread through the edges. The node vector distance problem is to estimate the distance traveled by the agent between two moments in time. This is closely related to the Optimal Transportation Problem (OTP), which has received attention in fields such as computer vision. OTP solutions can be used to solve the node vector distance problem, but they are not the only valid approaches. Here, we examine four classes of solutions, showing their differences and similarities both on synthetic networks and real world network data. The NVD problem has a much wider applicability than computer vision, being related to problems in economics, epidemiology, viral marketing, and sociology, to cite a few. We show how solutions to the NVD problem have a wide range of applications, and we provide a roadmap to general and computationally tractable solutions. We have implemented all methods presented in this article in a publicly available open source library, which can be used for result replication.
By exploiting variation both in mortgage payoffs and mortgage interest rate resets, we find that a decline in mortgage payments induces a significant increase in nondurable goods spending, even when households have substantial amounts of liquidity. Following mortgage payoff, households increase consumption expenditures by 61% of the original payment. In comparison, households increase consumption by only 36% in response to a transitory payment adjustment induced by interest rate changes. Households with a higher payment-to-income ratio have a significantly lower marginal propensity to consume (MPC). These results have practical implications for policy markers seeking to design consumption boosting policies and are important for understanding how changes in monetary policy may affect consumer spending patterns.
We use aggregated and anonymized information based on international expenditures through corporate payment cards to map the network of global business travel. We combine this network with information on the industrial composition and export baskets of national economies. The business travel network helps to predict which economic activities will grow in a country, which new activities will develop and which old activities will be abandoned. In statistical terms, business travel has the most substantial impact among a range of bilateral relationships between countries, such as trade, foreign direct investments and migration. Moreover, our analysis suggests that this impact is causal: business travel from countries specializing in a specific industry causes growth in that economic activity in the destination country. Our interpretation of this is that business travel helps to diffuse knowledge, and we use our estimates to assess which countries contribute or benefit the most from the diffusion of knowledge through global business travel.
As individuals specialize in specific knowledge areas, a society’s know-how becomes distributed across different workers. To use this distributed know-how, workers must be coordinated into teams that, collectively, can cover a wide range of expertise. This paper studies the interdependencies among co-workers that result from this process in a population-wide dataset covering educational specializations of millions of workers and their co-workers in Sweden over a 10-year period. The analysis shows that the value of what a person knows depends on whom that person works with. Whereas having co-workers with qualifications similar to one’s own is costly, having co-workers with complementary qualifications is beneficial. This co-worker complementarity increases over a worker’s career and offers a unifying framework to explain seemingly disparate observations, answering questions such as “Why do returns to education differ so widely?” “Why do workers earn higher wages in large establishments?” “Why are wages so high in large cities?”
The notion of skills plays an increasingly important role in a variety of research fields. Since the foundational work on human capital theory, economists have approached skills through the lens of education, training and work experience, whereas early work in evolutionary economics and management stressed the analogy between skills of individuals and the organizational routines of firms. We survey how the concept of skills has evolved into notions such as skills mismatch, skill transferability and skill distance or skill relatedness in labor economics, management, and evolutionary approaches to economics and economic geography. We find that these disciplines converged in embracing increasingly sophisticated approaches to measuring skills. Economists have expanded their approach from quantifying skills in terms of years of education to measuring them more directly, using skill tests, self-reported skills and job tasks, or skills and job tasks reported by occupational experts. Others have turned to administrative and other large-scale data sets to infer skill similarities and complementarities from the careers of sometimes millions of workers. Finally, a growing literature on team human capital and skill complementarities has started thinking of skills as features of collectives, instead of only of individuals. At the same time, scholars in corporate strategy have studied the micro-determinants of team formation. Combined, the developments in both strands of research may pave the way to an understanding of how individual-level skills connect to firm-level routines.
We explore optimal and politically feasible growth policies consisting of basic research investments and taxation. We show that the impact of basic research on the general economy rationalises a taxation pecking order with high labour taxes and low profit taxes. This scheme induces a significant proportion of agents to become entrepreneurs, thereby rationalising substantial investments in basic research fostering their innovation prospects. These entrepreneurial economies, however, may make a majority of workers worse off, giving rise to a conflict between efficiency and equality. We discuss ways of mitigating this conflict, and thus strengthening political support for growth policies.