Nafta and Its Effects on Robeson County

NAFTA And Its Effects On Robeson County, North Carolina by Russell D. Liggon

Economics 5150 Dr. Shi

NAFTA And Its Effects On Robeson County, North Carolina

Since being signed on January 1, 1994, NAFTA (North American Free Trade Agreement) has opened opportunities between the United States, Canada, and Mexico. NAFTA is considered by GDP standards the largest free trade area. In 2008, all tariffs between the countries involved were completely eliminated. From 1993 – 2009, trading cost has tripled from $297 billion to $1.6 trillion. According to an article History of NAFTA from http://useconomy.about.com, Article 102 of the NAFTA agreement states the reasons for its inception. 1. Eliminate barriers to trade and facilitate the cross-border movement of goods and services. 2. Promote conditions of fair competition. 3. Increase investment opportunities. 4. Create procedures for the resolution of trade disputes. 5. Provide protection and enforcement of intellectual property rights. 6. Establish a framework for further trilateral, regional and multilateral cooperation to expand NAFTA’s benefits. 7. Grant the signatories Most Favored Nation status. ¹The exports for the United States totaled $397 billion and their imports were $438 billion in 2009. The U.S. trade deficit with Canada and Mexico was $41 billion in 2009. In 2010, U.S. exports were $412 billion, and imports were $506 billion. The U.S. trade deficit with Canada and Mexico was $95 billion. Canada and Mexico became the second and third largest suppliers of imports of goods to the U.S. in 2010 with Canada having $276.5 billion and Mexico with $229.7 billion.

¹http://www.ustr.gov/trade-agreements/free-trade-agreements/north-american-free-trade-agreement-nafta

NAFTA And Its Effects On Robeson County, North Carolina Between the years 1994 – 2010, approximately 682, 900 jobs were lost to Mexico totaling $97.2 billion. 80% of the jobs lost in the United States were manufacturing. States that were hardest hit were New York, California, Michigan, and Texas to name a few. Wage rates among companies within the affected industries that stayed in the U.S. decreased by almost 50% between the periods of 1993 to 1995. Threats of moving the company overseas and the disapproval of unions were factors used by employers to decrease wages. One of the hardest places that were seriously affected by NAFTA was Robeson County, North Carolina. Robeson County is the largest county (by area) located in the Coastal Plains in the Southeastern part of North Carolina. According to the 2000 U.S. Census, the population was 123,339. The population is comprised of 38% Native American, 32% European, 25% African American, 5% Hispanic/Latino, and less than 1% Asian. The poverty rate is 24% and the illiteracy rate is 38%. These factors are strong causes for poor economic and social status in Robeson County. According to the NC Employment Security data, 8,708 manufacturing jobs were lost in Robeson County since 1993. From 1998 – 2003, 9 plant closings were reported. Manufacturing jobs in 1993 accounted for 31% of all jobs in Robeson County. By 2003, manufacturing jobs declined to only 18% of all jobs in Robeson County. Refer to the graph below for manufacturing job decline from 1990 – 2003. Manufacturing jobs declined from 17,430 in 1993 to 6,832 in 2003. These jobs were lost because of the cheap labor in Mexico and other countries overseas.

NAFTA And Its Effects On Robeson County, North Carolina The unemployment rate for Robeson County increased from 7.6% in 1990 to 9.1% in 2000. The breakdown by race for unemployment is as follows: Whites were 4.4% in 1990 and 6% in 2000; Blacks were 12.6% in 1990 and 16% in 2000; Native American was 9.3% in 1990 and 9% in 2000; Hispanic was 2.4% in 1990 and 12.4% in 2000. The per capita income for Robeson County in 2000 was $13,223.
Compared to the state’s annual income of $51,225 in 2000, Robeson County’s average income was $36,579 in 2000. 37% of households in Robeson County were below $20,000 per year. 52% of households were below $30,000 per year. Bankruptcies increased from 345 in 1999, to 498 in 2002 in Robeson County. Personal bankruptcies in the Eastern region of North Carolina increased approximately 4 times from 4,500 in 1994 to almost 15,000 in 2002. Older workers in Robeson County that lost their manufacturing jobs had a harder time of being re-hired. 30% of the population and 50% of the working population in Robeson County is in the 35-54 year age group.

NAFTA And Its Effects On Robeson County, North Carolina The dropout rate in Robeson County increased from 9% in 1990 to 11% in 200011% of the population has an associate or bachelor degree and 65% have a high school diploma. North Carolina State Center for Health Statistics conducted a survey in 2002 and found that 30% of the population did not have access to affordable healthcare. Infant mortality in Robeson County increased from 12.1% in 1990 to 14% in 2000. 31% of children under the age of 18 lived in poverty in 2000. 19% of white children under the age of 18 lived in poverty; 45% of African American children under the age of 18 lived in poverty; 26% of Hispanic children under the age of 18 lived in poverty; 26% of Native American children under the age of 18 lived in poverty. 9 single and 7 married individuals that were laid off from textile/manufacturing plants answered a questionnaire regarding the effects of being laid off from jobs that were relocated due to NAFTA. 6 individuals that had non-textile/manufacturing jobs were laid off were given the questionnaire to see if there are any significant similarities or differences with the answers. For the single individuals that were interviewed for this study, the salary (are weekly averages), for the single individuals with a college degree were higher than the single individuals with a high school diploma. After unemployment, the single individuals with a college degree earned more weekly than their counterparts with a high school diploma and less. Individuals that pursued more education/training after being unemployed was 50% of the single individuals interviewed. Respondent # 8 paid approximately $4,900 for education.

NAFTA And Its Effects On Robeson County, North Carolina Respondent # 6 incurred untold medical to her unemployment (stress, depression). Of the 9 respondents interviewed, 6 of the 9 did not have any dependents. Respondent # 6 was the only money earner for 5 dependents. The marriage was terminated due to the layoff. Respondent # 1 was the only earner with 3 dependents, and respondent # 3was the main earner with 3 dependents.

Respondent # | Medical Expense | Age | Education | More Education | Salary (Employed) | Salary (Laid Off) | 1 | No | 37* | H. School | Yes | $201 - $250 | $200 | 2 | No | 50 | 11th Grade | Yes | $301 - $350 | $200 | 3 | No | 40 | College | Yes | $301 - $350 | $250 - $300 | 4 | No | 56 | H. School | Yes | $$351 - $400 | $210 | 5 | No | 57 | College | No | $351 - $400 | $300 | 6 | Yes | 37** | High School | No | $301 - $350 | $225 | 7 | No | 31 | College | No | $400+ | $280 | 8 | No | 26 | High School | No | $400+ | $250 | 9 | No | 35 | 11th Grade | No | $301 - $350 | $230 |
Key indicators for single individuals affected by layoffs in Robeson County, North Carolina

NAFTA And Its Effects On Robeson County, North Carolina

Respondent # | Medical Expense | Age | Education | More Education | Salary (Employed) | Salary (Laid Off) | 1 | No | 35 | High School | Yes | $301 - $350 | $0 | 2 | No | 38 | College | Yes | $251 - $300 | $351 - $400 | 3 | Yes | 53 | College | Yes | $400+ | $400+* | 4 | No | 60 | College | No | $400 | $400+* | 5 | No | 39 | College | Yes | $400 | Retired | 6 | No | 45 | High School | Yes | $351 - $400 | $220 | 7 | Yes | 50 | College | yes | $400+ | $200 - $350 |
Key indicators for Married individuals affected by layoffs in Robeson County, North Carolina For the married individuals interviewed for this study, 4 out of 5 had a college education. One individual has a Master’s and one is in a Master’s program. 6 of the 7 individuals pursued more education/training after they were unemployed. The salary (weekly averages) was higher than their single counterparts when they were employed and unemployed. Respondent # 4 salary was unaffected because he had a second job. Respondent #5 was only unemployed for a short period of time and attained a job. She states suffering from stress and depression due to losing her job and adjusting to a new job with 50% of her former salary. Untold medical expenses did occur and her employer helped pay for expenses. Respondent # 7 suffered from headaches, leg, neck and back pain after being unemployed. He had to pay for medical expenses for his eye problems.
NAFTA And Its Effects On Robeson County, North Carolina Respondents # 4 and 6 have a household of 2 with 1 money earner. Respondents # 2, 3, and 7 have a household of 2 with 2 money earners. Respondent # 1 has a household of 3 with 1 money earner. Respondent has a household of 4 with 2 money earners.

Respondent # | Medical Expense | Age | Education | More Education | Salary (Employed) | Salary (Laid Off) | 1* | Yes | 40 | College | No | $400+ | $485 | 2 | No | 45 | High School | No | $201 - $250 | $110 | 3 | Yes | 19 | High School | Yes | Under $200 | $75 | 4 | No | 21 | High School | Yes | $201 - $250 | $0 | 5 | No | 23 | High School | Yes | $201 - $250 | $0 | 6 | No | 22 | High School | Yes | $201 - $250 | $0 |
Key Indicators for individuals that was laid off from jobs other than textile/manufacturer
*Only married individual interviewed from group pool Only one person that was interviewed had a weekly income above $400 and had a college degree. Five individuals had weekly income below $250. After they were unemployed, salaries declined by over 50% 4 of the 6 respondents pursued more education after they were unemployed. Respondent # 1 is the only one that incurred untold medical expenses due to unemployment (eye, dental, physicals). Respondent #5 household and money earner is 1. Respondents 2 and 3 have a household of 2 and 1 money earner. Respondents 1 and 6 have a house of 3 and 1 money earner. Respondent # 4 has a household of 4 and 1 money earner.

NAFTA And Its Effects On Robeson County, North Carolina On the last 2 pages is the Regression Analysis for the single respondents that were interviewed. The first analysis is for the respondents with a high school diploma with regards of income. The second analysis is for the respondents with a college degree with regards to income. The regressions were done to emphasize if having a higher education would factor the weekly salaries of the respondents interviewed. The first regression indicates an R Square of .314437 or 32%for the 6 respondents that have a high school diploma only. This indicates that there is a weak relation in regards to the education and salary of the respondents interviewed. The second regression indicates an R Square of .094219 or 9.4% for the 3 respondents with a college degree. The R Square is very small and weaker than the first regression. The coefficient for the first regression is 1.832104 which makes the independent variable almost as significant toward the dependent variable. The coefficient for the second regression is .771429 which makes the independent variable not significant toward the dependent variable. The t statistic for the first regression is 1.352624 which indicates the variable is less than accurate in regards to the dependent variable. The second t statistic of .32252 indicates the variable is not as accurate in regards to the dependent variable. In conclusion, NAFTA has had a negative effect on the workers in Robeson County, North Carolina. Of the respondents interviewed, their health and financial wellbeing have been affected. With the lack of suitable jobs, the jobs that are available offer a small salary. On the other hand, because of their situation, many respondents decided to go back to school for additional training for better jobs. Some of respondents with a college degree were lucky to attain one with a good salary as their former job. With the right attitude, the remaining respondents will attain a better job as well.
NAFTA And Its Effects On Robeson County, North Carolina

| | | | | | | | | | Regression Statistics | | | | | | | | | Multiple R | 0.560747 | | | | | | | | | R Square | 0.314437 | | | | | | | | | Adjusted R Square | 0.143046 | | | | | | | | | Standard Error | 59.28186 | | | | | | | | | Observations | 6 | | | | | | | | | | | | | | | | | | | ANOVA | | | | | | | | | | | df | SS | MS | F | Significance F | | | | | Regression | 1 | 6447.48 | 6447.48 | 1.834621 | 0.247039 | | | | | Residual | 4 | 14057.35 | 3514.338 | | | | | | | Total | 5 | 20504.83 | | | | | | | | | | | | | | | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | | Intercept | -62.7028 | 297.4363 | -0.21081 | 0.843339 | -888.518 | 763.1126 | -888.518 | 763.1126 | | X Variable 1 | 1.832104 | 1.352624 | 1.354482 | 0.247039 | -1.92338 | 5.587589 | -1.92338 | 5.587589 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | RESIDUAL OUTPUT | | | | PROBABILITY OUTPUT | | | | | | | | | | | | | Observation | Predicted Y | Residuals | Standard Residuals | | Percentile | Y | | | | 1 | 322.039 | 78.96095 | 1.489175 | | 8.333333 | 226 | | | | 2 | 303.718 | -77.718 | -1.46573 | | 25 | 335 | | | | 3 | 303.718 | 31.282 | 0.589967 | | 41.66667 | 335 | | | | 4 | 358.6811 | -23.6811 | -0.44662 | | 58.33333 | 335 | | | | 5 | 349.5206 | -14.5206 | -0.27385 | | 75 | 401 | | | | 6 | 395.3232 | 5.67679 | 0.107062 | | 91.66667 | 401 | | | |

NAFTA And Its Effects On Robeson County, North Carolina

SUMMARY OUTPUT | | | | | | | | | | | | | | | | | Regression Statistics | | | | | | | | Multiple R | 0.30695 | | | | | | | | R Square | 0.094219 | | | | | | | | Adjusted R Square | -0.81156 | | | | | | | | Standard Error | 44.74797 | | | | | | | | Observations | 3 | | | | | | | | | | | | | | | | | ANOVA | | | | | | | | | | df | SS | MS | F | Significance F | | | | Regression | 1 | 208.2857 | 208.2857 | 0.104019 | 0.801383 | | | | Residual | 1 | 2002.381 | 2002.381 | | | | | | Total | 2 | 2210.667 | | | | | | | | | | | | | | | | | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | Intercept | 150.4762 | 682.1751 | 0.220583 | 0.861786 | -8517.38 | 8818.333 | -8517.38 | 8818.333 | X Variable 1 | 0.771429 | 2.39188 | 0.32252 | 0.801383 | -29.6203 | 31.16314 | -29.6203 | 31.16314 | | | | | | | | | | | | | | | | | | | | | | | | | | | | RESIDUAL OUTPUT | | | | PROBABILITY OUTPUT | | | | | | | | | | | Observation | Predicted Y | Residuals | Standard Residuals | | Percentile | Y | | | 1 | 381.9048 | -6.90476 | -0.21822 | | 16.66667 | 335 | | | 2 | 362.619 | -27.619 | -0.87287 | | 50 | 375 | | | 3 | 366.4762 | 34.52381 | 1.091089 | | 83.33333 | 401 | | |

Works Cited 1. http://useconomy.about.com/od/tradepolicy/p/NAFTA_Problems.htm 2. http://democratheherald.com/converse-closing-chuck-taylor-all-star-plant/article 3. http://www.robesonian.com/articles/2006/09/18/news/story01.txt 4. http://www.ncsociology.org/hossfeld.htm 5. http://useconomy.about.com/od/tradepolicy/p/NAFTA_History.htm 6. http://www.ustr.gov/trade-agreements 7. http://www.mindtools.net/GlobCourse/formula.shtml 8. http://useconomy.about.com/od/grossdomesticproduct/p/GDP.htm 9. http://useconomy.about.com/od/economicindicators/a/GDP-statistics.htm 10. http://en.wikipedia.org/wiki/Gross_domestic_product 11. Managerial Economics 5150 Questionnaire’s