9422761 A longstanding issue in business cycle analysis is understanding how small shocks may produce large fluctuations in output. Recent theoretical research has shown how financial propagation mechanisms could amplify swings in spending and production caused by technology shocks or shifts in monetary. The theory begins with the idea, that for a significant class of borrowers (households, small and medium sized firms, etc.), information and enforcement problems may drive the cost of uncollateralized funds above the price of internal funds. Under these circumstances, borrowers' available supplies of collateral (broadly defined) and internal funds influence the terms of credit they face. In this way, borrowers' financial positions ultimately influence their spending and production decisions. The theory predicts that differences in cyclical behavior should emerge across classes of borrowers, depending on their respective access to credit, everything else equal. Credit market frictions are also more likely to impinge on behavior around recessionary periods, when borrowers have relatively weak balance sheets. To identify financial propagation effects, therefore, it is important to look at data across different phases of the business cycle, as well as across different classes of borrowers. This project will empirically assess financial propagation mechanisms using a newly available Census Bureau panel data for firms that contain both a rich cross-sectional dimension and a long time series dimension at the business cycle frequency to empirically assess financial propagation mechanisms. Unlike previously used firm level data sets, this data covers non-publicly as well as publicly traded firms for both manufacturing and other sectors, and has a long time series available at the quarterly frequency. More specifically, this project contributes to our understanding of financial propagation mechanisms in four ways: The first is a comprehensive descriptive ana lysis of the data for the manufacturing sector. The second involves structural estimation of inventory and investment demand equations to identify the influence of liquidity constraints in this sector. The third links the firm level data to Census Bureau plant level data to study the effects of financial factors on labor demand in manufacturing. The final project extends these efforts to the retail and wholesale trade sectors.
