10 The ordered responses are on a seven-point scale ranging from "not satisfied at all"to "completely satisfied."Consistent with our interest in the labor-income dimension of economic insecurity,this question measures perceptions of employment risks.We constructed the variable Insecurity by coding responses in the reverse order from the original question,with a range from 1 for individuals who give the response "completely satisfied"to a 7 for those individuals giving the response "not satisfied at all."Higher values of Insecurity thus indicate less satisfaction with job security. Our theoretical framework hypothesizes that high FDI activity in industries may generate economic insecurity among workers by increasing labor-demand elasticities.Theory does not offer clear guidance on how to measure this crucial concept of FDI exposure,so to test our key hypothesis we constructed three alternative measures. First,from the U.K.Office of National Statistics (ONS)we obtained data on inward and outward FDI investment positions in all 2-digit 1992 Standard Industry Classification (SIC92) U.K.industries from 1991 through 1999.3 The BHPS records respondent industry of employment by the 1980 Standard Industry Classification(SIC80),so we concorded the FDI data to 2-digit SIC80 industries.We then merged the industry-level FDI data with the BHPS survey. Our first,and main,measure of FDI exposure is a dichotomous industry-level variable FDI Presence.We set FD/Presence equal to one if two conditions were met:if the industry had any positive FDI investment,inward or outward,and if the industry's activities do not require 5 For his assistance in generating this data,we thank Simon Harrington. 6 The BHPS records industry of employment according to the SIC80 classification scheme in all years but does report this information according to the SIC92 system in two of the years in our sample
10 The ordered responses are on a seven-point scale ranging from “not satisfied at all” to “completely satisfied.” Consistent with our interest in the labor-income dimension of economic insecurity, this question measures perceptions of employment risks. We constructed the variable Insecurity by coding responses in the reverse order from the original question, with a range from 1 for individuals who give the response “completely satisfied” to a 7 for those individuals giving the response “not satisfied at all.” Higher values of Insecurity thus indicate less satisfaction with job security. Our theoretical framework hypothesizes that high FDI activity in industries may generate economic insecurity among workers by increasing labor-demand elasticities. Theory does not offer clear guidance on how to measure this crucial concept of FDI exposure, so to test our key hypothesis we constructed three alternative measures. First, from the U.K. Office of National Statistics (ONS) we obtained data on inward and outward FDI investment positions in all 2-digit 1992 Standard Industry Classification (SIC92) U.K. industries from 1991 through 1999.5 The BHPS records respondent industry of employment by the 1980 Standard Industry Classification (SIC80), so we concorded the FDI data to 2-digit SIC80 industries.6 We then merged the industry-level FDI data with the BHPS survey. Our first, and main, measure of FDI exposure is a dichotomous industry-level variable FDI Presence. We set FDI Presence equal to one if two conditions were met: if the industry had any positive FDI investment, inward or outward, and if the industry’s activities do not require 5 For his assistance in generating this data, we thank Simon Harrington. 6 The BHPS records industry of employment according to the SIC80 classification scheme in all years but does report this information according to the SIC92 system in two of the years in our sample
11 producers and consumers to be in the same geographic location.If either of these conditions were not met,we coded FDI equal to zero.As with all our FDI measures,FDI Presence varies by both industry and year. Our logic in defining FD/Presence with these two conditions runs as follows.The first condition of positive FDI investment is straightforward.Any inward or outward FDI activity satisfies this.The second condition recognizes that FDI activity is less likely to alter labor- demand elasticities if business activities cannot be outsourced across countries because the consumer and producer must be in the same geographic location. Consider the examples of wholesale trade,retail trade,and personal services (e.g.,haircuts). The large majority of business activities in these industries require the co-location of producers and consumers:e.g.,customers sitting in the barber's chair.The notions of economic insecurity related to FDI that we discussed in Section 2 focus on the substitutability of business activities across countries.In reality,in many industries,FDI does not have this characteristic;indeed, FDI may arise precisely because foreign customers cannot be served at a distance via international trade.Accordingly,FD/Presence identifies not all industries with FDI,but instead only those industries with FDI in which business activities can be outsourced across countries. So for industries such as wholesale trade,retail trade,and personal services we coded FDI Presence as zero regardless of the level of actual FDI. It is theoretically ambiguous if,in addition to the existence of FDI activity,the magnitude also matters.It may be that more FDI activity indicates greater capital mobility,which in turn raises labor-demand elasticities and perceptions of employment risks.Since the dichotomous FDI Presence does not distinguish FDI magnitudes once any FDI is present,we also constructed two continuous measures of FDI exposure that account for magnitudes relative to industry size
11 producers and consumers to be in the same geographic location. If either of these conditions were not met, we coded FDI equal to zero. As with all our FDI measures, FDI Presence varies by both industry and year. Our logic in defining FDI Presence with these two conditions runs as follows. The first condition of positive FDI investment is straightforward. Any inward or outward FDI activity satisfies this. The second condition recognizes that FDI activity is less likely to alter labordemand elasticities if business activities cannot be outsourced across countries because the consumer and producer must be in the same geographic location. Consider the examples of wholesale trade, retail trade, and personal services (e.g., haircuts). The large majority of business activities in these industries require the co-location of producers and consumers: e.g., customers sitting in the barber’s chair. The notions of economic insecurity related to FDI that we discussed in Section 2 focus on the substitutability of business activities across countries. In reality, in many industries, FDI does not have this characteristic; indeed, FDI may arise precisely because foreign customers cannot be served at a distance via international trade. Accordingly, FDI Presence identifies not all industries with FDI, but instead only those industries with FDI in which business activities can be outsourced across countries. So for industries such as wholesale trade, retail trade, and personal services we coded FDI Presence as zero regardless of the level of actual FDI. It is theoretically ambiguous if, in addition to the existence of FDI activity, the magnitude also matters. It may be that more FDI activity indicates greater capital mobility, which in turn raises labor-demand elasticities and perceptions of employment risks. Since the dichotomous FDI Presence does not distinguish FDI magnitudes once any FDI is present, we also constructed two continuous measures of FDI exposure that account for magnitudes relative to industry size