By J. M. Lane
Foreign-Trade Zones in the U.S.
My presentation concerns a topic that has remained largely unknown by the majority of the population and has not been researched greatly by the academic community. The title of my paper is the “Spatial & Temporal Impact of Foreign-Trade Zones on Economic Development in the United States”
Introduction
So, what is a foreign-trade zone?
Foreign-trade zones are designated areas in the United States where products and materials are categorized as foreign until they enter the U.S. market. Private businesses don’t pay tariffs, excise taxes, duties or ad-valorem state taxes on materials within a zone. According to former congressman Emanuel Celler, “the foreign-trade zone for all intents and purposes is foreign territory.”
Today, FTZs exist in every state and businesses can warehouse, assemble, or manufacture goods within their designated site location. Rules are strict for people and products entering a zone. Each zone is guarded by Customs officers and surrounding by 6-gage metal fencing and 12.5 gage barbed-wire.
The white map in the center shows the service area for FTZ 230 in Greensboro and the map on the bottom right shows the Deere-Hitachi manufacturing site in Kernersville.
The picture above the service area map shows the barbed-wire fencing surrounding the Deere-Hitachi site and the large map to the right shows the location of that site.
So, what’s the stated purpose of foreign-trade zones? According to the Foreign-Trade Zone Board, FTZs are designed to promote exports, provide US firms with a competitive advantage, and increase local development. This paper focuses on the last one on the list.
This Study
In this study I ask two main questions: Is there a spatial relationship between foreign-trade zones and economic development patterns across the US? And, once established, do foreign-trade zones impact short-term or long-term economic growth rates?
The first question deals with a spatial issue, so I used Geographically Weighted Regression as a tool to answer this question. GWR measures spatial changes in relationships between two or more variables. A gaussian weight matrix was used in the model. The map on the center of the slide gives you an idea of how gaussian weights are applied across space. Once performed, the GWR models provided local statistics for each observation. A total of 258 zones were included in this analysis and dependent variables were measured on the county-scale.
The next question requires longitudinal data, but due to data limitations, this analysis only goes back to 2010. In this portion, I analyzed short-term and long-term impacts on economic output once a foreign-trade zone was established in a particular county.
Short-term impacts were determined by measuring the percentage change between data from the year before and the year after an FTZ was added, and long-term impacts compared data from the year before and three years after.
After that, percentage growth rates from counties that established an FTZ were compared to first-order and second-order contiguous counties to see if there were any major differences in growth rates. The two maps on the right show the observations included in this portion. The counties in the dark blue are counties that added an FTZ, the standard-blue counties neighbor FTZ-counties, and light blue counties are second-order contiguous
After evaluating differences between mean values for each group of counties, one-sample t-tests were performed on each group to determine if growth rates were significantly different from zero. I followed this analysis by running a Kruskal-Wallis non-parametric test to see if there were any significant differences between county groups.
Variables Included
This slide shows the variables used in both analyses. Three separate GWR models were performed for median household income, unemployment rates, and number of manufacturing firms. Each model had five independent variables gathered from each county’s foreign-trade zones.
The temporal analysis focuses specifically on the percentage changes in median incomes, unemployment rates, number of manufacturing firms, and manufacturing employment in a county before and after the introduction of a foreign-trade zone.
GWR Results
GWR results suggest a significant but uneven relationship between FTZ variables and spatial development patterns.
Within the median household income model, roughly 30 percent of the variation is explained by the independent variables. However, the map on the left shows major spatial variability in this relationship. Local R-squared values vary from a low of 0.0074 to a high of 0.909. Significant patterns appear around the Mississippi and Ohio river watersheds, and along the west coast region.
There were similar r-squared values in the Unemployment Rate model, which explained 36 percent of the variation. Local R-squared values ranged from a low of 0.005 to a high of 0.711. As you can see from the map in the center of the slide, the higher r-squared values occurred along the Mississippi and Ohio river watersheds, coastal Alaska, and in the desert southwest.
The Manufacturing firm model had the most significant results between the three, with a mean r-squared of 0.73. However, this model had the highest variation in local r-squared values of the three models, with a low r-squared value of 0.052 and a high of 0.995.
As you can see from the map on the right, highest r-squared values occurred in the western portion of the continental US (especially along the Mexican border), across most of Alaska, part of Hawaii, coastal Texas, the Florida peninsula, and around lake Michigan.
Coefficient estimates for each model varied significantly across space but due to time limits, I’ll move on to the next portion.
Temporal Results
If FTZs actually promote local economic development, then a pattern should occur where group 1 counties would have noticeably higher growth rates than surrounding counties. Or, in the case of unemployment rates, a higher negative growth rate.
So, these bar graphs show differences in long-term and short-term growth rates for each variable between county groups.
Short-term growth rates suggested that there was no discernible impact from FTZs on median household income. However, there are noticeable differences in unemployment rates between group 1 counties and groups 2 and 3.
On average, counties adding FTZs saw a 4.7 percent decline in unemployment rates compared to a 1.7 percent increase in group 2 and a 0.4 percent decline in group 3.
A similar trend occurred with manufacturing firms. On average, counties that added FTZs had a 3.4 percent short-term growth rate in the number of manufacturing firms compared to -1.3 percent in group 2 counties and 1.9 percent in group 3.
Manufacturing employment growth rates were only slightly higher than neighboring counties with a 1.1 percent increase in FTZ counties compared to 0.9 percent increase and 0.5 percent decline in surrounding counties.
Long-term impacts were similar in every variable except for manufacturing employment. FTZs had very little impact on median household income compared to surrounding counties.
Long-term impacts on unemployment were interesting, in that of the three groups, unemployment actually declined in FTZ counties when it increased in surrounding counties.
The opposite trend occurred with manufacturing firms. FTZ-counties saw an increase of 0.8 percent while surrounding counties lost manufacturing firms.
As far as the long-term impact on manufacturing employment is concerned, mean values show a positive impact for counties establishing FTZs compared to surrounding counties, with a 7.5% increase in long-term growth.
T-Test & Kruskal-Wallis Results
One-sample t-test results indicate both short-term and long-term growth rates in median household income for all three county groups were significantly different from zero.
Unlike median income, none of the other short-term growth rates were significant. However, Long-term unemployment, manufacturing firms, and manufacturing employment growth rates were significantly different from zero in some counties. Interestingly, unemployment rates significantly increased and manufacturing firms significantly declined in counties neighboring FTZ-counties, while manufacturing employment significantly increased in FTZ-counties.
Results from the Kruskal-Wallis test indicate the only significant difference in economic growth between counties occurred in long-term manufacturing employment. While neighboring counties saw a significant increase in long-term unemployment and a significant decline in manufacturing firms, there were no significant differences between county groups.
Discussion
Okay, so what does all this mean?
As far as spatial impacts are concerned, there is a strong but varied relationship between FTZs, median household income, unemployment rates, and manufacturing firms. This suggests that FTZs may have an impact on spatial development patterns. In other words, FTZs may be leading to agglomeration and attracting foreign-direct investment, all of which can lead to capital flight from other regions that don’t benefit from FTZs. These results coincide with research I recently published in the Southeastern Geographer focusing specifically on the southeast.
The GWR results also suggest that physical landscapes may play a role in this relationship as well. Results were much stronger around major waterways such as the Mississippi, and Ohio rivers and coastal areas. This would make sense, as more cargo and merchandise enter high trafficked areas and major port infrastructure. The largest mercantile cities are also located along these waterways.
As mentioned earlier, local r-squared values were higher for manufacturing firms along the Mexican border and this may be due to trade agreements like NAFTA and USMCA, which were designed with manufacturing in mind.
Initial results from the temporal analysis suggest that adding an FTZ to a county has no discernible short-term impacts on income or manufacturing employment. However, it appears that FTZs may have a positive impact on overall employment and the number of manufacturing firms.
This suggests that FTZs may have a spillover effect into other sectors of the economy. In other words, FTZs may increase overall employment but they do not lead to higher manufacturing employment in the short-term.
Long-term trends were similar in unemployment rates and manufacturing firms; however, long-term growth rates in manufacturing employment were higher in FTZ counties than surrounding counties, suggesting that it may take longer for FTZs to impact manufacturing jobs than jobs in other industries.
T-test results suggest that adding an FTZ can result in a significant increase in the unemployment rates and decline in the number of manufacturing firms in neighboring counties. This implies that manufacturing and non-manufacturing firms either migrate to FTZ counties or close their doors all-together.
Kruskal-Wallis results suggest that the only variable positively affected by the addition of an FTZ compared to surrounding counties was long-term manufacturing employment growth rates. Counties adding an FTZ had a 10.14% increase in manufacturing employment compared to neighboring counties.
Results from the spatial and temporal analyses imply that FTZs have had some impacts on spatial development patterns and longitudinal economic growth, but these impacts vary greatly across space and time. In areas where FTZs impacted development patterns, it may have led to spatial inequality and uneven development. And when it comes to impacts over time, FTZs may have helped in some ways, but, adding an FTZ has caused more damage in neighboring counties than it has helped in associated counties.
The only net positive from adding an FTZ is an increase in long-term manufacturing employment growth, but no significant differences occurred in income. More manufacturing jobs were available in counties adding an FTZ, but employment in neighboring counties declined over the long-term in both manufacturing and all other job sectors.
Results from this paper, and information that I’ve found in another paper that I recently finished, has led me to conclude that foreign-trade zones may help some people, but most people see very little benefit. In many cases, people are being negatively affected. So, who really benefits?
It appears that a few geographic regions, primarily large urban areas along major shipping routes, and a short-list of major corporations have benefited from FTZs, but the vast majority of the population has not.
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