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Do unions discourage economic activity?
Economics Letters North-Holland
25 (1987) 373-377
373
DO UNIONS DISCOURAGE
ECONOMIC
ACTIVITY?
*
John S. HEYWOOD Uniuersity
of Wisconsin-Milwaukee,
Milwaukee,
WI 53201, USA
Michael D. DEICH Congressional
Budget Office, Washington,
Received 29 July 1987 Final version received 26 October
DC 20515, USA
1987
Previous examinations of the influence of unions on economic activity fail to use a measure of unionization that varies both by state and industry. Such a failure introduces the possibility of serious specification errors, a possibility confirmed by comparing traditonal estimates which suggest unions depress a state’s economic activity with new estimates which reveal no such effect.
1. The problem A large, recently developed literature explores the determinants of economic activity across states. While researchers typically focus on state and local tax rates, many include measures of unionization in both their discussions and testing equations. In every instance the variable used is the percent of the state’s workforce belonging to labor unions. This variable is so general that the specifications presented leave us unpersuaded that unions play a role in determining a state’s economic activity. We contend that much more can be learned by using a union measure that varies both by state and by industry. Previous authors assume the current degree of unionization within a state estimates the probability a new plant will become unionized upon entering. If unions increase firm costs, higher expected production costs will be associated with more unionized states. As a consequence, firms building new plants will choose states with low degrees of unionization, other things equal. Indeed, most authors are able to confirm this prediction at least in part [see Neuman (1983), Plaut and Pluta (1983), Bartik (1984) and Wasylenko and McGuire (1986)]. Typically, separate industry regressions are run with the dependent variable being some measure of economic activity within the states. The most popular dependent variable appears to be the percentage change in employment with other choices including the changes in capital stock, in value added and in the number of plants. The variation in the dependent variable across states is then explained by a list of independent variables ranging from as few as three to as many as 25. The most typical regressors include state fuel costs, state expenditures, taxes, whether the state has right-to-work laws, and the percent of work force unionized. For example, Neuman (1983) confirms a significant negative correlation between unionization and employment change in four of a dozen two-digit industries using just unionization, right-to-work, and tax rates as regressors. * Special appreciation
O165-1765/87/$3.50
is expressed
to Yongtao
Jin for valuable
0 1987, Elsevier Science Publishers
research
assistance
B.V. (North-Holland)
and to Robert
Drago
for helpful comments.
314
J.S. Heywood, M.D. Deich / Do unions discourage economic actiuity?
Results such as Neuman’s potentially suffer from two simple, but serious, econometric errors casting the results in doubt. First, the unionization measure is highly aggregated. It is not specific to the particular industry the regressions are based on. This classic errors-in-variables problem arises whenever the regressor used is the desired regressor plus an error term. As a consequence, estimates are biased toward no result. To the extent that the errors-in-variables problem is serious, finer unionization data on an industry by state basis would improve the estimates and demonstrate an even more important role for unionization in discouraging economic activity. On the other hand, with a topic as complex as business location one is always concerned with omitted variables correlated both with state-wide unionization and economic activity. There are specific reasons for this concern. Many U.S. firms cannot avoid unions merely by moving to a state with a lower overall unionization rate. Automobile plants in Tennessee and steel plants in Alabama are nearly as likely to be unionized as their equivalents in Michigan and Pennsylvania, The degree of unionization is, in very large part, a characteristic of the industry [see Belman (1985)]. Certain states have lower rates of unionization precisely because the composition of their economies avoids the set of unionized industries, not because those industries are non-union within their state. This realization suggests that if plants from a unionized industry open in a predominantly non-union state, they have done so for reasons other than avoiding the union. These reasons may include other dimensions of ‘business climate’ in the state and may not be easily captured in the included regressors. Yet, the partial correlation with the state-wide degree of unionization may turn up significant because of a hidden correlation between state-wide unionization and business climate. Absent the full determinants of the location decision, this problem is alleviated by focusing on the degree of each state’s unionization by industry. In other words, the hidden correlation between unionization and business climate may be removed by using industry specific data. A firm knowing any plant in its industry would be unionized regardless of location would then not appear to be moving because of a lower state-wide unionization rate. We suspect the two problems of errors-in-variables and omitted variable bias have opposite effects in previous work. The first problem suggests the true effect of unions on economic activity has been underestimated, A proper measure that varied by industry should demonstrate stronger results. The second problem suggests the true effect of unions has been overestimated. If the union measure varied by industry, the chance of a spurious negative correlation between unionization and economic activity would be reduced. 2. Methodology To examine the issues we create a data set which includes unionization on a state by industry basis. The fact that such a variable is not routinely available forces us to constrain the study in several ways. First, our study uses the industry definitions of the Current Population Survey (CPS). We select seven three-digit disaggregate industries with reasonable sample size. Second, in order to match the available employment data we use a sample from 1971 to 1978. During this period the CPS identifies the state of residence only for those living in one of twelve major states. All others are identified only by region. As a result, we constrain ourselves to these major states. To increase the sample size and so the reliability of our new unionization estimates we pool three years of the May CPS, 1973-1975. The estimates of the percent of the industry unionized in each of twelve major states is presented in table 1. In general the estimates seem reliable, but the small samples in a few of the cells should be noted. The simple correlations between these estimates and the state-wide estimates used by others range from 0.411 to 0.881. We base the dependent variable on employment change between the years in the sample by first creating three-year averages of employment for the six years (1972-1977) and each of the seven
315
J.S. Heywood, M.D. Deich / Do unions discourage economic actiuity? ‘Table 1 Percent of industry
unionized
158 NY
197
45.8
NJ
37.5
46.2
46
88
78
CT
MA
28.8
21.1
19.4
12
73
19
67
25.0
38.6
34.6
70
52
50.0
47.9
IN
IL
50.0
36.0
44
91
46.8
34.1
62
88
7.1
NC
4.8
18.1
11.8
23.8
72
85
42 21.7
structural
Electrical
metal products;
machinery;
219 -
25.5
27
98
52.0
21.6
25
51
64.2
58.3
61
72
7.1
2.2
27.8
72.8
electrical; 319 -
4.0
72
25
13.3
14.5
105
55
16.2
92 except
9.1 11
19.4
15.5
and equip.;
34.3 169
89
36
335
vehicles
48.1
70
197 - Machinery, Motor
78.2
5
2.9
143
84
40.0
19.1 46
20.8
17.9
87
14
46
Fabricated
publishing
6.1
21.0
154
60.9
17
33
21
111
208 -
24.8
32
70.6
74.7
149
40.6
45
162
25
49.5
CA
68.0
33.1
37.8
18
321
150
157
53
4.0
TX
60.5
100
61.1
5
176
162
3.8
28 FL
43
26.0
64.3
80.0
42.6
55.8
215
96
91
235
86
23.5
23.1
162
69.8
166
233
61.3
32
51.4
28.3
356
75.0
235
58.3
8 OH
32.5
339
54.2
88
172
43
319
72.7
202
37.2
44.5 157
219
37.6
96
41.3
102
208
25.0
105
57.8
PA
207
31.4
48
equip.;
average. a
Industry
State
a 158 -
in major states, 1973-1975
19.7
136 207 Apparel
Radio,
142 T.V.
and communication
and accessories;
339 -
Printing,
and allied fld.
industries. Then, the percentage change between years becomes the dependent variable yielding five years of data (197331977) for each major state and industry. We aggregate employment data from the Survey of Manufactures to fit as closely and consistently as possible to CPS industry definitions. Following the literature, we introduce controls for the existence of right-to-work laws, a relative measure of fuel cost which varies by state, year and industry, and proportional measures of tax and expenditures which vary by state and year.
3. Results The first regression estimates use the average state unionization (Union-l) as a regressor. This is the average of the three years (1973-1975) across all industries in the particular states taken from the
316 Table 2 Comparing
J.S. Heywood, M.D. Deich / Do unions discourage economic activity?
regressions
Variable
Union-l
R-squared Union-2
R-squared
with aggregate
and specific measures
of unionization.
a
Industry 158
197
207
208
219
319
339
- 0.199 (0.790)
- 0.142 (0.214)
- 0.499 (2.204)
- 0.029 (0.125)
- 0.798 (2.683)
-0.184 (2.842)
- 0.258 (1.608)
0.134
0.090
0.381
- 0.075 (0.717)
- 0.025 (0.222)
- 0.0545 (0.719)
0.132
0.090
0.332
0.184
0.316 -0.010 (0.173) 0.352
a Note the dependent variable is the percentage change in employment T-statistics are in parentheses and all regressions include a constant Complete results are available from the authors.
- 0.875 (1.000) 0.092
0.157 - 0.056 (0.244) 0.157
and the number of observations and the independent variables
0.171 0.094 (0.942) 0.146 is 60 in all regressions. mentioned in the text.
CPS. As the upper part of table 2 demonstrates, this measure is a significant partial correlate in three of seven cases and close to significance in an additional case. In all of these cases the Union-l coefficient is reasonably large and negative. For example, in the motor vehicle industry (219) a ten percent increase in the state’s degree of unionization results in an eight percent decrease in state employment within that industry. The other results are of similar magnitude with coefficients ranging from about 0.2 to 0.8. These results mirror those of Neuman (1983) and others. The hypothesis that unionization deters economic activity within a state receives support in some industries but not in others, while in some cases it is difficult to tell whether unions should be considered important or not (such as industry 339). We now run the same regressions with the more accurate measure of unionization (Union-2) which varies by both industry and state. These new regressions can be taken as a test of which of the two potential specification errors is more fundamental. The lower part of table 2 presents a consistent outcome to such a test. In all but one industry the point estimate on the union variable falls dramatically when one uses the new measure. Moreover, the coefficient on the new measure does not even approach significance in any of the regressions and some signs are even positive. The superior union measure fails to confirm the supposed role of unions in discouraging economic activity.
4. Conclusions Our tests highlight the perils of using aggregated measures of unionization in addressing the correlation between unions and economic activity. The aggregate measure could easily correlate with excluded business climate variables giving rise to spurious results. This seems especially likely given the known interstate similarity in the degree of unionization within several industries, suggesting firms move for reasons unrelated to unions. While the aggregate measure performed as expected from earlier research, we find no hint of an independent role for unions using the industry specific measure. Future research addressing the role of unions in regional economic activity must consider this as a warning against using highly aggregate union measures.
J.S. Heywood, M.D. Deich / Do unions discourage economic activity?
311
References Bar&, Timothy, 1984, Business location decisions in the United States: Estimates of the effects of unionization, taxes and other characteristics of states, Working paper no. 84-W05, Feb. (Vanderbilt University, Nashville, TN). Belman, Dale, 1985, Firm resistance to unionization: The direct and indirect effects of industry structure on union membership and wages, Unpublished dissertation (University of Wisconsin-Madison, Madison, WI). Carlton, Dennis, 1983, The location and employment choices of new firms: An econometric model with discrete and continuous endogenous variables, Review of Economics and Statistics 65, no. 3, 440-449. McLure, Charles, 1970, Taxation, substitution and industrial location, Journal of Political Economy 78, no. 1, 112-132. Neuman, Robert, 1983, Industry migration and growth in the South, Review of Economics and Statistics 65, no. 1, 76-86. Plaut, Thomas and Joseph Pluta, 1983, Business climate, taxes and expenditures, and state industrial growth in the United States, Southern Economic Journal 50, no. 1, 99-119. Schmenner, Richard, 1982, Making business location decisions (Prentice-Hall, Englewood Cliffs, NJ). Wasylenko, Michael and Therese McGuire, 1985, Jobs and taxes: The effect of business climate on states’ employment growth rates, National Tax Journal 38, no. 4, 497-511.
25 (1987) 373-377
373
DO UNIONS DISCOURAGE
ECONOMIC
ACTIVITY?
*
John S. HEYWOOD Uniuersity
of Wisconsin-Milwaukee,
Milwaukee,
WI 53201, USA
Michael D. DEICH Congressional
Budget Office, Washington,
Received 29 July 1987 Final version received 26 October
DC 20515, USA
1987
Previous examinations of the influence of unions on economic activity fail to use a measure of unionization that varies both by state and industry. Such a failure introduces the possibility of serious specification errors, a possibility confirmed by comparing traditonal estimates which suggest unions depress a state’s economic activity with new estimates which reveal no such effect.
1. The problem A large, recently developed literature explores the determinants of economic activity across states. While researchers typically focus on state and local tax rates, many include measures of unionization in both their discussions and testing equations. In every instance the variable used is the percent of the state’s workforce belonging to labor unions. This variable is so general that the specifications presented leave us unpersuaded that unions play a role in determining a state’s economic activity. We contend that much more can be learned by using a union measure that varies both by state and by industry. Previous authors assume the current degree of unionization within a state estimates the probability a new plant will become unionized upon entering. If unions increase firm costs, higher expected production costs will be associated with more unionized states. As a consequence, firms building new plants will choose states with low degrees of unionization, other things equal. Indeed, most authors are able to confirm this prediction at least in part [see Neuman (1983), Plaut and Pluta (1983), Bartik (1984) and Wasylenko and McGuire (1986)]. Typically, separate industry regressions are run with the dependent variable being some measure of economic activity within the states. The most popular dependent variable appears to be the percentage change in employment with other choices including the changes in capital stock, in value added and in the number of plants. The variation in the dependent variable across states is then explained by a list of independent variables ranging from as few as three to as many as 25. The most typical regressors include state fuel costs, state expenditures, taxes, whether the state has right-to-work laws, and the percent of work force unionized. For example, Neuman (1983) confirms a significant negative correlation between unionization and employment change in four of a dozen two-digit industries using just unionization, right-to-work, and tax rates as regressors. * Special appreciation
O165-1765/87/$3.50
is expressed
to Yongtao
Jin for valuable
0 1987, Elsevier Science Publishers
research
assistance
B.V. (North-Holland)
and to Robert
Drago
for helpful comments.
314
J.S. Heywood, M.D. Deich / Do unions discourage economic actiuity?
Results such as Neuman’s potentially suffer from two simple, but serious, econometric errors casting the results in doubt. First, the unionization measure is highly aggregated. It is not specific to the particular industry the regressions are based on. This classic errors-in-variables problem arises whenever the regressor used is the desired regressor plus an error term. As a consequence, estimates are biased toward no result. To the extent that the errors-in-variables problem is serious, finer unionization data on an industry by state basis would improve the estimates and demonstrate an even more important role for unionization in discouraging economic activity. On the other hand, with a topic as complex as business location one is always concerned with omitted variables correlated both with state-wide unionization and economic activity. There are specific reasons for this concern. Many U.S. firms cannot avoid unions merely by moving to a state with a lower overall unionization rate. Automobile plants in Tennessee and steel plants in Alabama are nearly as likely to be unionized as their equivalents in Michigan and Pennsylvania, The degree of unionization is, in very large part, a characteristic of the industry [see Belman (1985)]. Certain states have lower rates of unionization precisely because the composition of their economies avoids the set of unionized industries, not because those industries are non-union within their state. This realization suggests that if plants from a unionized industry open in a predominantly non-union state, they have done so for reasons other than avoiding the union. These reasons may include other dimensions of ‘business climate’ in the state and may not be easily captured in the included regressors. Yet, the partial correlation with the state-wide degree of unionization may turn up significant because of a hidden correlation between state-wide unionization and business climate. Absent the full determinants of the location decision, this problem is alleviated by focusing on the degree of each state’s unionization by industry. In other words, the hidden correlation between unionization and business climate may be removed by using industry specific data. A firm knowing any plant in its industry would be unionized regardless of location would then not appear to be moving because of a lower state-wide unionization rate. We suspect the two problems of errors-in-variables and omitted variable bias have opposite effects in previous work. The first problem suggests the true effect of unions on economic activity has been underestimated, A proper measure that varied by industry should demonstrate stronger results. The second problem suggests the true effect of unions has been overestimated. If the union measure varied by industry, the chance of a spurious negative correlation between unionization and economic activity would be reduced. 2. Methodology To examine the issues we create a data set which includes unionization on a state by industry basis. The fact that such a variable is not routinely available forces us to constrain the study in several ways. First, our study uses the industry definitions of the Current Population Survey (CPS). We select seven three-digit disaggregate industries with reasonable sample size. Second, in order to match the available employment data we use a sample from 1971 to 1978. During this period the CPS identifies the state of residence only for those living in one of twelve major states. All others are identified only by region. As a result, we constrain ourselves to these major states. To increase the sample size and so the reliability of our new unionization estimates we pool three years of the May CPS, 1973-1975. The estimates of the percent of the industry unionized in each of twelve major states is presented in table 1. In general the estimates seem reliable, but the small samples in a few of the cells should be noted. The simple correlations between these estimates and the state-wide estimates used by others range from 0.411 to 0.881. We base the dependent variable on employment change between the years in the sample by first creating three-year averages of employment for the six years (1972-1977) and each of the seven
315
J.S. Heywood, M.D. Deich / Do unions discourage economic actiuity? ‘Table 1 Percent of industry
unionized
158 NY
197
45.8
NJ
37.5
46.2
46
88
78
CT
MA
28.8
21.1
19.4
12
73
19
67
25.0
38.6
34.6
70
52
50.0
47.9
IN
IL
50.0
36.0
44
91
46.8
34.1
62
88
7.1
NC
4.8
18.1
11.8
23.8
72
85
42 21.7
structural
Electrical
metal products;
machinery;
219 -
25.5
27
98
52.0
21.6
25
51
64.2
58.3
61
72
7.1
2.2
27.8
72.8
electrical; 319 -
4.0
72
25
13.3
14.5
105
55
16.2
92 except
9.1 11
19.4
15.5
and equip.;
34.3 169
89
36
335
vehicles
48.1
70
197 - Machinery, Motor
78.2
5
2.9
143
84
40.0
19.1 46
20.8
17.9
87
14
46
Fabricated
publishing
6.1
21.0
154
60.9
17
33
21
111
208 -
24.8
32
70.6
74.7
149
40.6
45
162
25
49.5
CA
68.0
33.1
37.8
18
321
150
157
53
4.0
TX
60.5
100
61.1
5
176
162
3.8
28 FL
43
26.0
64.3
80.0
42.6
55.8
215
96
91
235
86
23.5
23.1
162
69.8
166
233
61.3
32
51.4
28.3
356
75.0
235
58.3
8 OH
32.5
339
54.2
88
172
43
319
72.7
202
37.2
44.5 157
219
37.6
96
41.3
102
208
25.0
105
57.8
PA
207
31.4
48
equip.;
average. a
Industry
State
a 158 -
in major states, 1973-1975
19.7
136 207 Apparel
Radio,
142 T.V.
and communication
and accessories;
339 -
Printing,
and allied fld.
industries. Then, the percentage change between years becomes the dependent variable yielding five years of data (197331977) for each major state and industry. We aggregate employment data from the Survey of Manufactures to fit as closely and consistently as possible to CPS industry definitions. Following the literature, we introduce controls for the existence of right-to-work laws, a relative measure of fuel cost which varies by state, year and industry, and proportional measures of tax and expenditures which vary by state and year.
3. Results The first regression estimates use the average state unionization (Union-l) as a regressor. This is the average of the three years (1973-1975) across all industries in the particular states taken from the
316 Table 2 Comparing
J.S. Heywood, M.D. Deich / Do unions discourage economic activity?
regressions
Variable
Union-l
R-squared Union-2
R-squared
with aggregate
and specific measures
of unionization.
a
Industry 158
197
207
208
219
319
339
- 0.199 (0.790)
- 0.142 (0.214)
- 0.499 (2.204)
- 0.029 (0.125)
- 0.798 (2.683)
-0.184 (2.842)
- 0.258 (1.608)
0.134
0.090
0.381
- 0.075 (0.717)
- 0.025 (0.222)
- 0.0545 (0.719)
0.132
0.090
0.332
0.184
0.316 -0.010 (0.173) 0.352
a Note the dependent variable is the percentage change in employment T-statistics are in parentheses and all regressions include a constant Complete results are available from the authors.
- 0.875 (1.000) 0.092
0.157 - 0.056 (0.244) 0.157
and the number of observations and the independent variables
0.171 0.094 (0.942) 0.146 is 60 in all regressions. mentioned in the text.
CPS. As the upper part of table 2 demonstrates, this measure is a significant partial correlate in three of seven cases and close to significance in an additional case. In all of these cases the Union-l coefficient is reasonably large and negative. For example, in the motor vehicle industry (219) a ten percent increase in the state’s degree of unionization results in an eight percent decrease in state employment within that industry. The other results are of similar magnitude with coefficients ranging from about 0.2 to 0.8. These results mirror those of Neuman (1983) and others. The hypothesis that unionization deters economic activity within a state receives support in some industries but not in others, while in some cases it is difficult to tell whether unions should be considered important or not (such as industry 339). We now run the same regressions with the more accurate measure of unionization (Union-2) which varies by both industry and state. These new regressions can be taken as a test of which of the two potential specification errors is more fundamental. The lower part of table 2 presents a consistent outcome to such a test. In all but one industry the point estimate on the union variable falls dramatically when one uses the new measure. Moreover, the coefficient on the new measure does not even approach significance in any of the regressions and some signs are even positive. The superior union measure fails to confirm the supposed role of unions in discouraging economic activity.
4. Conclusions Our tests highlight the perils of using aggregated measures of unionization in addressing the correlation between unions and economic activity. The aggregate measure could easily correlate with excluded business climate variables giving rise to spurious results. This seems especially likely given the known interstate similarity in the degree of unionization within several industries, suggesting firms move for reasons unrelated to unions. While the aggregate measure performed as expected from earlier research, we find no hint of an independent role for unions using the industry specific measure. Future research addressing the role of unions in regional economic activity must consider this as a warning against using highly aggregate union measures.
J.S. Heywood, M.D. Deich / Do unions discourage economic activity?
311
References Bar&, Timothy, 1984, Business location decisions in the United States: Estimates of the effects of unionization, taxes and other characteristics of states, Working paper no. 84-W05, Feb. (Vanderbilt University, Nashville, TN). Belman, Dale, 1985, Firm resistance to unionization: The direct and indirect effects of industry structure on union membership and wages, Unpublished dissertation (University of Wisconsin-Madison, Madison, WI). Carlton, Dennis, 1983, The location and employment choices of new firms: An econometric model with discrete and continuous endogenous variables, Review of Economics and Statistics 65, no. 3, 440-449. McLure, Charles, 1970, Taxation, substitution and industrial location, Journal of Political Economy 78, no. 1, 112-132. Neuman, Robert, 1983, Industry migration and growth in the South, Review of Economics and Statistics 65, no. 1, 76-86. Plaut, Thomas and Joseph Pluta, 1983, Business climate, taxes and expenditures, and state industrial growth in the United States, Southern Economic Journal 50, no. 1, 99-119. Schmenner, Richard, 1982, Making business location decisions (Prentice-Hall, Englewood Cliffs, NJ). Wasylenko, Michael and Therese McGuire, 1985, Jobs and taxes: The effect of business climate on states’ employment growth rates, National Tax Journal 38, no. 4, 497-511.