These are the new finding of the working paper of the Asian Development Bank titled The Impact of Exchange Rate on FDI and the Interdependence of FDI over Time by Joseph D. Alba, Donghyun Park, and Peiming Wang.

The paper examines the impact of exchange rates on foreign direct investment (FDI) inflows into the United States in the context of a model that allows for the interdependence of FDI over time. Interdependence is modeled as a two-state Markov process where the two states can be interpreted as either a favorable or an unfavorable environment for FDI in an industry. Unbalanced industry-level panel data from the US wholesale trade sector are used in the analysis and yield two main results.

Common sense tells us that the real exchange rate has an effect on FDI, just as it has an effect on international trade. A number of theoretical and empirical studies have examined the relationship between FDI and the real exchange rate more formally.

In particular, Campa develops an empirically testable model of FDI based on Dixit’s model of investment, which in turn is derived from the theory of option pricing in financial economics. Campa’s model predicts, and the empirical evidence from his Tobit estimation strongly supports, a significant effect of the real exchange rate on the probability of FDI entry in US wholesale trade industries.

However, using the ZIP model, Tomlin fails to find a meaningful relationship between the exchange rate and the average rate of FDI. Our study expands the ZIP model, tells the researchers in their concluding remarks, by incorporating the possibility of interdependence of FDI over time in each industry. To do so, we use the MZIP model, which is based on two-state Markov chains. For empirical purposes, we extend the MZIP model, which is a time-series specification, for panel data since we use industry-level panel data for our empirical analysis. While our data are based largely on Campa, there are some differences.

It is also important to point out that we use an unbalanced panel data set.

One of our two main empirical findings is that FDI is indeed interdependent over time.

Such interdependence captures immeasurable and uncertain factors that affect the state of an industry—whether firms view an industry as favorable or unfavorable to FDI—and, in turn, these views may be affected by the state of the industry in the previous period. As mentioned earlier, corporate rivalry may explain such interdependence. Our second main empirical finding is that when industries are favorable to FDI, the exchange rate level has a positive and highly significant impact on the rate of FDI inflows. This implies that a stronger host-country currency may make investment more profitable for foreign investors who enjoy an increase in their home-country currency revenues.

Further findings are that the other two exchange rate-related variables are not significant and both measures of sunk costs have significant negative effects on FDI.

If FDI is interdependent over time, a model such as the MZIP model that explicitly accounts for such interdependence is more appropriate for the empirical analysis of FDI.

Our evidence does indeed provide strong support for the interdependence of FDI over time. Our study thus suggests that the ZIP model may be inappropriate for the analysis of panel FDI data since it may result in incorrect inferences about parameters. In line with Campa’s findings but in contrast to Tomlin’s findings, we find that the exchange rate level has a significant effect on the rate of FDI inflows into the US. Although there are theoretical grounds for both a positive and negative effect of the exchange rate on FDI, in the case of the US wholesale trade sector, our results clearly lend support to a positive effect. This implies that a stronger US dollar will promote FDI inflows into the US wholesale trade sector. At a broader level, our analysis points to a need for future researchers to incorporate possible interdependence in FDI over time when they examine the determinants of FDI. Doing so will strengthen the robustness of their findings.#