NAFTA has increasingly become politicised in the US in recent years, and with this, there has been heightened speculation on its purpose for ordinary Americans and if it is in their best interests after all. Using US Census data, Gaston and Trefler’s (1997) regression model is then applied to estimate the effects of NAFTA on the employment and wage growth of 14 US manufacturing sectors in years 1994-2015. IPUMS is then used to measure these effects by geography at a county-level.
The results show a clear relationship between NAFTA’s tariff reductions and employment losses, with highly-tariffed industries pre-NAFTA experiencing the biggest declines in employment levels and slowest wage growth. The findings also align well with Heckscher-Ohlin’s (1967) trade theory, showing a clear link between trade liberalisation and stagnant wage growth in some sectors, with migration from Mexico magnifying these effects. The rust belt is then identified as the region which has felt these adverse effects the most, with sunbelt states subsequently profiteering in a North-South manufacturing shift.
The study then makes recommendations on the re-implementation of trade tariffs with both Mexico and Canada, finding that this would increase employment levels and stimulate wage growth.
Chapter 1: Introduction
In 1990, the North American Free Trade Agreement (NAFTA) was declared and agreed in principle by 1992, finally ratified under President Clinton’s administration in 1994, to the dismay of many sceptical Americans, including political contender Ross Perot. NAFTA removed most tariffs between the US, Canada and Mexico and essaypro.com/dissertation/examples/economics-examples/nafta-mexico-canada.php">liberalised trade amongst the new bloc. Consequently, many corporations took advantage of the cheaper supply of labour in neighbouring Mexico and here began the relocation of plants and manufacturing facilities, resulting in many job losses. Critics of NAFTA argue that the agreement was introduced only to benefit multi-national corporations, bolstering their outsourcing capabilities and reducing costs; all at the expense of the American working classes. These feelings of resentment have only grown, evident with the nomination of President Trump in 2016. With this, came key announcements regarding NAFTA, the first a new 20% tax on all imported lumber from Canada, a clear deviation from NAFTA principles; and the second, a complete renegotiation of NAFTA with Mexico and Canada. Subsequently, this dissertation will investigate the impact NAFTA has had on manufacturing employment and wages since its induction, also exploring if specific regions in the US have been disproportionately affected by the agreement.
- To explore the effects of NAFTA’s trade barrier eradication on employment and wages in the manufacturing industry between 1994 and 2015
- To determine if NAFTA’s impact on the local labour market is affected by geographical factors
Applied research will be used for the dissertation, utilizing Gaston and Trefler’s (1997) regression model. This will calculate what effects different NAFTA independent variables have had on manufacturing employment and wages. These variables vary from concessionary tariff rates to levels of migration. Before this, an in-depth review of existing literature will first be explored, commencing in chapter 2.
Chapter 2: Literature Review
Studies investigating essaypro.com/essays/economics/the-nafta-has-produced-net-benefits-for-business-in-canada-mexico-and-the-usa-economics-essay.php">the effects of NAFTA have proven drastically different results and conclusions, with the overall consensus of critics regarding the agreement being very divided. Going back to the inception of NAFTA, Nystrom et al. (1995) set about creating a strategic cost analysis tool for companies planning to exploit the new trade deal, whilst Wylie (1995) made estimates for the potential implications that NAFTA could have on North America’s manufacturing trade with the rest of the world. Both critics offer a stark contrast in viewing the agreement, one more positive in the interest of multi-national corporations, and the other vastly direr for blue-collar workers in the manufacturing industry. These opposing sides of the spectrum set the tone for the literature review, which will use work from a wide range of authors on NAFTA and evaluate how these findings contribute to the existing academic research available.
NAFTA’s effects on employment and wages in manufacturing
Predictions on the effects of NAFTA on wages and employment in the manufacturing industry were divisive even in its initial stages, with Hufbauer and Schott (1993) estimating that in its first year, NAFTA would produce a net growth of 171,000 jobs, whilst Koechlin and Larudee (1992) projected a 490,000 loss in US manufacturing jobs in years 1992 to 2000, caused by a shift in investment to Mexico. (Cited in Sunthonkhan, 2010, p.9) In addition, Weintraub (1992) and Brown (1992) saw NAFTA as being of little significance to overall US GDP growth, with surveys suggesting that a maximum of 0.5% growth could be expected in the US, 2% in Canada and 7% in Mexico. Similarly, Hinojosa-Ojeda et al. (2000) also highlighted the minor impact of NAFTA on US manufacturing employment, finding that trade with NAFTA partners provided net 23,220 jobs per year.
Wylie (1995) goes a step beyond this, using Houthakker and Magee’s (1969) estimates of elasticity of import demand for manufactured goods in the US and NAFTA-related GDP growth predictions to project total import growth. Subsequently, Wylie’s (1995) calculations pointed towards a 0.85% growth in imports, suggesting that NAFTA-induced employment and trade growth outweighs the negative effects of investments moving, primarily, to Mexico. Whilst Wylie attempted to make growth estimates more dynamic and therefore reliable by using elasticity of import demand to measure future trends, his work remained incomplete due to a number of omitted factors in his calculations. For example, he did not consider how NAFTA could reduce business environment uncertainty, and how as a result, more US corporations would be stimulated to undertake trade and production rationalisation, also possibly resulting in companies increasing their vertical integration capabilities in new, accessible markets. As a result, intermediate goods traded within NAFTA markets would see high levels of growth due to corporations utilizing multinational plants and manufacturing facilities to achieve further economies of scale. Wylie (1995) opted to use Baldwin and Murray’s (1977) partial equilibrium economic model for trade creation as well as Bhagwati’s (1992) and Kreinin and Plummer’s (1992) models for trade diversion. These measured only static production levels, not taking into account dynamic production rationalisation. (See appendices) Consequently, the validity of the results can be questioned as the evidence cited by Wiley (1995) does not measure the trade effects of NAFTA accurately.
The complexity of predicting the effects of NAFTA on trade, employment and wages in the US was not fully comprehended by researchers, and there is still no clear consensus on the impact of NAFTA on the US, even with 20 years’ worth of data. This is evident in Kondonassis et al. (2008), which analyses 22 manufacturing industries of the two-digit Standard Industrial Classification (SIC), estimating that up to 500,000 jobs have been lost in the US a result of NAFTA, with a large bulk of these being highly paid manufacturing jobs. Despite this, they argue that the trade liberalisation has not affected wage levels in the US, a point which is contended by Polaski (2006), who suggests that employee bargaining power had been reduced as a result of NAFTA, negatively affecting their wage growth. Similarly, Lawrence et al. (2003) argues that trade liberalisation has impacted less educated, blue collar workers in the manufacturing industry the hardest, who according to estimations, have seen a 12% decline in real wages since 1973. Mclaren and Hakobyan (2015) results develop on this, finding that blue collar workers in the worst affected manufacturing industries saw significantly slower wage growth (Welfare gains estimated at 0.2%) compared to other sectors. They continue by linking income equality to NAFTA, finding that while manufacturing workers had seen their wages significantly decrease, US corporations witnessed an 88% in profit growth in the 1990’s, with CEO wages also increasing by over 460%.
Other researchers observe that shrinking wages in manufacturing are caused by technological advancements, not trade liberalisation. Lavoie and Therrien (1999) suggest that low skilled manufacturing employees have been mostly displaced by high-tech machinery, reducing demand for these workers, also seeing a shift to high-skilled labourers instead. Conversely, Wood (1995), Cline (1997) and Leamer (1996) examine a connection between trade liberalisation and declining wages of manufacturing workers. (Cited in Yasin, 2009, p. 48) These conclusions in general are aligned with the Heckscher-Ohlin trade theory, which proposes that increased import competitiveness reduces demand for domestic unskilled manufacturing workers by way of cheaper products produced by less costly unskilled labour the exporting country. (Ohlin, 1967) This is reinforced by Swagel and Slaughter (1997), who suggest that NAFTA increases the supply of unskilled labour in the US, therefore reducing wages for domestic, low skilled manufacturing workers through outsourcing or through accelerated immigration of unskilled labourers from Mexico into an increasingly competitive US labour market.
Whilst many of these authors all agree on the same basic conclusion, the models and concepts used to reach them are all different, for example Wylie (1995) uses a partial equilibrium model adapted from Baldwin & Murray (1977), while Yasin (2009) uses factor-content and price-effect approaches, indicating that these results are not interchangeable with each other as each model can give a different outcome even with the exact same data.
Geographical factors affecting level of impact
According to Holmes (1996), the historical location of the manufacturing belt in the North occurred simply by chance, and inevitably, manufacturers will move South to more favourable natural climates for production. He uses the cotton textile industry to study this effect, finding that the lowest quality producers begin to re-locate first to exploit better growing conditions and increased cost savings. Subsequently, other firms follow suit to achieve similar effects while suppliers also begin to re-locate to meet increased demand in new Southern territories. Holmes’ (1996) outline of firm re-location can also be extrapolated for use on NAFTA, as this opened up trade with Mexico, essentially broadening the Southern border for firms looking to relocate. Figure 1 shows a map of the traditional manufacturing regions.
Holmes’ theory is reinforced by Casetti’s (1984) findings, which show that employment in manufacturing saw a sharp drop in the rust belt region and New England in the 1970’s, whilst at the same time, Sunbelt regions in the South saw a rapid increase in manufacturing employment, signalling a clear re-location of manufacturing from North to South. This trend accelerated throughout the decade, with later work from Casetti & Jones (1987) confirming this, also suggesting that the rustbelt to sunbelt swing actually began in the 1960’s. Logan (2008) reaffirms this in Figure 2, signalling a clear shift from manufacturing belt states to sunbelt states.
However, there is evidence of selective data bias in Holmes’ (1996), this is evident in his decision to analyse the cotton industry for his research, an industry whose production he would have known would be affected by differing climates. If he analysed a more diverse set of industries, such as the automobile or air conditioning industries, his results would have been vastly different, thus not aligning with his pre-determined narrative. Similarly, Glasmeier & McCluskey (1987) suggest that reasons for production relocation are industry-specific and that a natural shift to better climates in the South is not a primary reason for this. Yet, despite its flaws, Holmes’ (1996) cotton example can also apply to this theory as well, as this proves that each industry is unique in its requirements; cotton production needing a favourable climate for better yields. Glasmeier & McCluskey (1987) also found that automobile manufacturers moved their parts assembly operations away from the rust belt and closer to vital markets to the South and West. Glasmeier & Leichenko (1996) develop on this by observing a correlation between increased trade liberalisation and relocation of manufacturing from the rust belt to the South, where supply of unskilled labour was much larger, beginning with Mexico’s entry into the GATT in 1985. (General Agreement on Trade and Tariffs) As a result, the rustbelt and Midwestern states suffered the most in manufacturing employment and wages, harbouring most of the 3m job losses in years 1979-1992, while Southern regions accounted for only 3% of these. Yet, this trend only repeated itself once more and was accelerated by NAFTA, seeing jobs leave the rust belt as well as Southern regions, beyond US borders, to Mexico.
Yoskowitz et al. (2002) investigate this theory, examining levels of manufacturing employment in 7 Southern Texas counties between 1990 to 1997. Their findings indicate that these seven border counties had experienced much higher levels of employment growth pre-NAFTA, crediting Mexico’s 1985 entry into the GATT (General Agreement on Tariffs and Trade) for these previously high levels of growth. However, despite the sudden drop in employment growth post-NAFTA, Yoskowitz et al. (2002) do not associate the two with each other, instead citing the reduced growth as a natural decrease from 1985’s high. They also suggest that counties do not benefit significantly from their proximity to the border as most of the trade done here moves through these regions and into bigger cities, such as Houston.
This is contended by McCallum’s (1995) research, which observed 30 US states and 10 Canadian regions along the joint border, investigating for location effects of producers within close proximity to the border. It found that counties located close to the border benefitted from increased trade with their neighbours, as did producers, concluding that this can also be applied to the US-Mexico border, expecting even more impressive trade patterns due to differences in resources and labour. Hanson (1995) also looks at how corporations are increasingly moving assembly plants overseas, specifically to Mexico. He predicted that NAFTA tariff reductions would result in firms moving plants and factories to regions near the US/Mexico border for transportation cost saving reasons. He also finds a correlation between offshore assembly firms and employment growth in border towns, consistent with McCallum’s (1995) research.
Chapter 3: Methodology
An adapted form of Gaston & Trefler’s (1997) regression model for employment and wages will be used for the first objective’s research, testing for the manufacturing employment and wage effects of NAFTA tariff reductions between 1994-2015. The model used is shown below:
yis = θs + βCA∆τ + βUS∆τ + εis,
The equation shows yis as the result for industry wages and employment, whilst βCA∆ is for industry-specific independent variables; βUS∆ demonstrates independent variables which can be used across all industries.
Tariffs against Mexico and Canada are the most important variables tested in this research, these will be dependent on each industry. As tariffs have all but been removed between NAFTA countries, tariff concessions will be used to estimate the present-day effects they would have on employment and wages. They will be calculated using Schott’s (2004) method of dividing total duties amassed by the overall taxable value of imports. Data used for these calculations will be from the US Census Bureau and the Centre for International Data. (2006) A negative relationship between removing tariffs and manufacturing employment is expected, whilst wages in high skilled jobs are anticipated to grow as a result of a higher supply of low skilled labour.
Trade flows to and from Canada and Mexico will also be variables, these will use import and export values to the US, quantifying any changes in trade between NAFTA participants. Naturally, it is expected that removing trade barriers such as tariffs has resulted in higher levels of trade with Mexico and Canada after NAFTA. It is likely that Canadian imports have impacted US manufacturing employment and wages positively, due to the similarities between both countries capabilities in labour and resources. Imports from Mexico are thought to show a negative correlation with employment, more so than on wages, specifically damaging low skilled jobs, with a high number of these outsourced.
Migration variables from Mexico and Canada are used to investigate the effects of imported labour from both nations, with high skilled labourers expected from Canada and low skilled from Mexico. Both legal immigrants and estimates of illegal immigrants are included in the data, with illegals likely to be composed of low skilled workers. Migration from Mexico is expected to be positive for employment growth as there would be more supply for low skilled workers, but for the same reason, Mexican migration is expected to be a negative factor for wage growth. Canadian migration is projected to have an indifferent effect on wages and employment.
The next variable is labour productivity; this is used to measure both wage growth and employment levels. As tariffs and supply of labour are made more accessible, productivity is expected to increase and with this wages, both at the expense of employment. Data is extracted from the IPUMS (Integrated Public Use Micro Data Series) database for this.
GDP and Interest rates
As US GDP increases, it is predicted that demand for labour follows the same direction, increasing wages and employment. Whilst a decrease in GDP would mean a decline in employment due to less capital expenditure available to companies and lower wages. Gaston and Trefler (1997) also suggest that interest rates can affect employment levels, with high rates acting as barriers to corporations looking to borrow capital to expand their operations.
14 2-digit SIC manufacturing sectors were chosen for the study, with data collected for years 1994 to 2015, the IPUMS database was used to compile the data. See Table 1. (IPUMS,2017)
For the research objective regarding geographical factors and how they affect NAFTA’s impact, the sample data was collected from all 3,007 US counties for employment, whilst only partial county data was used for analysing wages, with the remaining data used from state statistics from the US Census Bureau. County shares of manufacturing earnings and employment were collected from the US department of commerce online resources. (USDC, 2017) The research is expected to align with previous literature, showing a concentration of employment losses in the traditional rust belt region of the US.
Chapter 4: Empirical results
NAFTA’s effects on employment and wages in manufacturing
Most notably, results in Table 1 suggest that tariffs with Mexico could impact employment positively, whilst small changes in tariffs with Canada would affect imports but not affect employment significantly. The results indicate that exports to Canada supported employment slightly, whilst an increase in imports did the opposite in a big way, negatively impacting employment considerably. These effects were perpendicular to those for Mexico, whose imports were the most important growth factor for manufacturing employment, while exports to Mexico were damaging employment rates. Also, as anticipated, Mexican migration to the US had an adverse effect on manufacturing employment, whilst Canadian migration continued to stimulate employment.
Table 2 measures NAFTA effects on manufacturing wages. The results show that exports to Mexico had the most weight on influencing higher wages, also indicating a positive relationship between the two. However, imports from Mexico signalled a more negative impact, though the findings also suggest that Mexican migration increased average manufacturing wages, contrary to much research. Conversely, Canadian migration is shown to affects wages negatively, also finding that tariffs with Canada would reduce wages. The evidence also shows that manufacturing wages were especially sensitive to changes in tariffs with Canada, with results indicating that a hypothetical 1% reduction in Canadian tariffs could increase wages by 3.3%.
Subsequently,to build on these findings, Table 3 looks at how different levels of tariffs affected employment in manufacturing industries after NAFTA.
Source: Dataset from IPUMS
The findings from Table 3 show employment figures from 1994-2015 for 14 two digit SIC industries. For low tariff manufacturing industries, there was an average job loss of 129,142, equal to a 15% decrease in employment after NAFTA came into effect. Moreover, NAFTA tariff cuts were made proportionally, meaning that the most highly tariffed sectors would be impacted the most. As a result, previously highly tariffed sectors lost on average 19.3% more job losses than low tariff sectors, seeing a 34.3% average fall in employment since 1994, with the clothing and textiles industries suffering 82% and 72% reductions, in the same order. It is also notable that these two sectors are composed of mostly low-skilled labour, meaning that the jobs lost were most likely outsourced to Mexico, where corporations can cut costs per employee and benefit from NAFTA tariff cuts. Only the food production and metals fabrication sectors were able to withstand NAFTA’s tariff adjustments, with an average of 0.8% employment growth between the two.
Source: Dataset from IPUMS
In line with poor employment performance, the clothing production sector also experienced the lowest wage growth in all 14 analysed industries, increasing only $627 or 4.1% within a 21-year timeframe. This suggests that as well as outsourcing clothing production, companies have also seen cheaper, imported low-skilled labour take up positions within the US, significantly impacting wages negatively. In comparison, other sectors saw average wages grow by $11,294, with low tariff sectors seeing wages grow by 8 percentage points more than that for high tariff sectors. In addition, the data in Table 4 shows that the NAFTA tariff cuts significantly supported the Lumber industry’s wage growth at 69%. Canada is the primary exporter of Lumber to the US, suggesting that tariff cuts between the two has fuelled wage growth beyond that of all other sectors, hence a positive correlation between the two, as seen also in Table 2. Furthermore, low-tariff industries show the strongest levels of correlation between job losses and wage growth, whilst high tariff sectors show more mixed results. Also, the metals fabrication and food production industries have been the most resilient since NAFTA’s inception, showing stable signs of employment and high levels of wage growth.
Location effects of NAFTA
Figure 3 is a map of 3,007 US counties, measuring rates of employment between NAFTA’s commencement in 1994 to 2015, using data from the US Census Bureau and IPUMS. As expected, the biggest job losses were experienced in the manufacturing belt, an area stretching from Wisconsin to Western New York, whilst the greatest gains were seen in the Southern states of Texas and Florida.
Counties most affected by NAFTA were located in Wisconsin, Michigan, Indiana, Pennsylvania, Ohio and New York, which saw an average manufacturing employment reduction of 29%, or 89,437 jobs. The biggest decline in manufacturing employment was seen in Noble county, Indiana, with a 59% drop in employment. Brewster county, Texas and Marion county in Florida saw the highest levels of manufacturing employment growth, averaging at 17.3% between them, with generally higher levels of growth correlated with the Southern geographic areas. Another reason for this is that the rust belt states were very reliant on manufacturing for employment, meaning that they would be affected the most by tariff adjustments. Figure 4 conveys share of manufacturing employment per county. There is a relatively high correlation between a county’s share of employment from manufacturing and the ensuing job losses experienced in years 1994-2015, with prime examples Indiana and Ohio, who had 27 and 19 counties each with 20% or more jobs in manufacturing. Of these manufacturing-reliant counties, more than 80% of them were rural.
Southern states, on the other hand, experienced an influx of corporations moving in with plants and factories to exploit cheaper low skilled labour and to take advantage of proximity effects near new supply chains, thereby bolstering the effects of vertical integration.
Figure 5’s results are concurrent with those in Table 4, with 26 states seeing manufacturing wages grow by 41-45%, 13 states 35-40%, 10 states 46-55% and Texas with a 57.1% average wage growth since NAFTA came into effect. In line with the other results, wage growth is generally greater in regions with most job losses, more specifically the rust belt region, with Ohio, Michigan, Pennsylvania, Indiana and Wisconsin collectively seeing an average manufacturing wage growth of 43.5%. Moreover, the Southern states of Texas and Florida once again see positive signs of growth, with a 53.3% averaged wage growth between them.
Figure 5 Manufacturing Wage growth by state; 1994-2015
Wage growth shows some signs of correlation with the average share of wages coming from manufacturing in each county. 48% (1465) of all US counties had earnings from manufacturing account for 10% or more of their total incomes, with a majority of these in the East and South Eastern pockets of the country and Texas in the South. See Figure 6
Chapter 5: Discussion
NAFTA’s impact on US manufacturing employment and wages
The findings of this research regarding the trade agreement’s impact on manufacturing employment and wages suggest that the trade liberalisation pacts of NAFTA have affected previously high-tariffed industries the most, with these sectors experiencing the lowest levels of wage growth and shedding the highest number of jobs in years 1994-2015. The regression results indicate that re-introducing tariffs with Mexico could slow employment losses down and increase wages in the most severely affected sectors, such as clothing production and textiles manufacturing. Employment and wages in low-skilled labour abundant manufacturing sectors have also been harmed by Mexican migration and outsourcing, which has allowed corporations to exploit cheaper labour. This is consistent with Heckscher-Ohlin’s trade theory. (Ohlin,1967) Unexpectedly, the results also show that imposing tariffs against Canada would increase employment levels, especially in highly traded US-Canada sectors such as Lumber. This would also soften the negative effects of Canadian imports on US employment levels, however, wages would suffer as a result of tariffs with Canada. Overall, the conclusions align with those from Swagel and Slaughter (1997), Cline (1997) and Leamer (1996), whose findings also bring into question the benefits of NAFTA for the United States.
Regional effects of NAFTA
The results confirm prior predictions that the rust belt region was hit the hardest by NAFTA, experiencing the highest job losses in the US. It also found that counties with the highest shares of earnings and employment attributable to manufacturing were worst affected. Many of these were near to the Canadian border, dispelling Yoskowitz et al’s (2002) theory of favourable location effects of counties closer to the borders of trading partners. However, the research finds that the rust belt region recovered well in regards to wage growth, seeing an average 43.5% wage growth since 1994. Moreover, the results also show a clear shift in employment from rustbelt to sunbelt states, concurrent with Logan’s (2008) illustrations and Glasmeier and McCluskey’s (1987) work, which suggests that manufacturing has been moving South as a result of trade liberalisation and a larger supply of cheap, unskilled labour. Subsequently, the Sunbelt states of Texas and Florida were found to have benefitted the most from trade liberalisation, seeing the highest levels of manufacturing employment and wage growth, possibly due to the influx of cheaper imported labour from Mexico in the 1990’s.
The main limitations experienced in the study lie with difficulties in data collection and time restraints which meant that further exploratory research could not be conducted. To develop, whilst county-level data was collected, compiled and mapped out for employment, wage growth data on a county-by-county basis was unattainable and only available to US students/scholars. As a result, the wage growth map was limited to a state level analysis, meaning that results for this section lacked the specificity of the employment section and consequently, may be defined as incomplete or even unreliable. In addition, time restraints also meant that regions could not be analysed to find out which industries had primarily been causing employment losses. Moreover, recent literature on the location/geographical effects of trade liberalisation also proved to be insufficient, with dated work the only viable option.
Additional research is required to fully comprehend the effects of NAFTA on manufacturing employment and wages and the regions most affected by this. A recommendation for future researchers would be to analyse a longer timeframe, perhaps from 1980(Before GATT and NAFTA). This would allow for a more comprehensive look into the conditions before NAFTA and give researchers the opportunity to compare before and after NAFTA, rather than estimating how tariffs would affect employment and wages in the present day. Also, future research should also explore which specific industries affected levels of employment within different geographical regions.
Chapter 6: References
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Trade Creation equation – TCi = MP,LSi( T* – TO) / ( 1 +K”)
Trade diversion equation – TDi = MNPi(TCi/Vi)