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  5. Network and Spatial Dynamics in Macroeconomics
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Network and Spatial Dynamics in Macroeconomics

Paper Session

Sunday, Jan. 7, 2024 8:00 AM - 10:00 AM (CST)

Convention Center, 305
Hosted By: American Economic Association
  • Chair: Xiaohan Ma, Texas Tech University

Endogenous Network Under Incomplete Information

Victor Monteiro
,
Insper
Diogo Guillen
,
Central Bank of Brazil
Thiago Christiano Silva
,
Central Bank of Brazil

Abstract

We develop an endogenous production network economy model coupled with incomplete information, where the degree of information at the firm-level is the engine of the network formation and distorts both producers’ decision and the aggregate allocations of the economy. To tie this relationship, we consider
that producers find their suppliers through a decentralized search given their level of information, in
which firms become more or less informed depending on how edges far they know of the equilibrium production network. In our model, we establish the existence, uniqueness and efficiency of the network
equilibrium for a given level of information, and show that the higher the level of information, (i) the
more stable the network, (ii) the lower the density of the network, and (iii) the higher the spillover
impact of a productivity shock on the aggregate output. We also design an optimal contract to show that the combination of information-enhancing policies and tax-subsidies is able to mimic a Walrasian full information equilibrium. Finally, we use a proprietary dataset that covers a large share of Brazilian
financial transactions and simulate our model with it.

Ghosts of Trade Routes Past: Pre-Colonial Networks and Persistence in Modern Trade

Conrad Copeland
,
University College London

Abstract

This paper studies the persistence of pre-colonial trade relationships on modern trade and development in Africa. I construct a newly digitised and geo-referenced dataset of historical trade posts and routes for pre-colonial Africa. The paper tests the impact of several features of these historical trade networks including the presence, connectedness, and size of trade hubs as well as the connections themselves on modern trade flows between countries. I find that these historical trade links have significant persistent effects. Historical network inclusion is quantitatively similar to other institutional trade links, with trade nearly doubling for countries within the same network. This is found to increase with both the country’s level of integration and the prominence of the historical trade hub within the pre-colonial networks. Importantly, there are also significant agglomeration effects with modern economic activity concentrating around more prominent historical trade hubs.

Learning and Expectations in Dynamic Spatial Economies

Jingting Fan
,
Pennsylvania State University
Sungwan Hong
,
Pennsylvania State University
Fernando Parro
,
Pennsylvania State University

Abstract

The impact of shocks in dynamic environments depends on how forward-looking agents anticipate the path of future fundamentals that shape their decisions. We incorporate flexible beliefs about future fundamentals in a general class of dynamic spatial models, allowing beliefs to be evolving, uncertain, and heterogeneous across groups of agents. We show how to implement our methodology to study both ex-ante and ex-post shocks to fundamentals. We apply our method to two settings—an ex-ante study of the economic impacts of climate change, and an ex-post evaluation of the China productivity shock on the U.S. economy. In both cases, we study the impact of deviations from perfect foresight on different outcomes.

The Network Origins of Transport Costs: Evidence from Developing Economies

Michael Olabisi
,
Michigan State University

Abstract

Building on a model of network formation for the transport modes that support international trade, the paper explains why transport costs for international trade are higher on average for firms in developing countries. The model's predictions of higher costs for countries outside the central clusters of global trade network are tested on international trade data, as well as data on international fares for air connections to the US. The data also confirms predictions that are consistent with other papers on the long-term decline in transport costs - especially for air transport.

Trade Shocks and Job Growth: A Network Model Perspective

Michael Olabisi
,
Michigan State University
Jiawen Liu
,
Michigan State University

Abstract

Fluctuations in economic growth in foreign countries affect the U.S. economy, primarily through trade. We present a simple network model of trade and growth that formally represent the mechanisms through which demand shocks in other countries affect economic activities in the US. The key model prediction is that as the US trades more with emerging markets, whose economic volatility is higher on average, US employment volatility too will increase. The model predictions are estimated using US trade data and sector-level aggregate economic data from other countries over the past two decades.
JEL Classifications
  • E3 - Prices, Business Fluctuations, and Cycles