wished to use the AFLQ rather than the FLQ, then a slightly higher value of would need to δ be chosen at the outset. It is evident that both approaches reviewed here have merits and demerits, which should be borne in mind when deciding which one to pursue. One should also be aware that, with Bonfiglio’s method, the estimated declines with regional size, whereas Flegg and Tohmo’s δ method exhibits a positive relationship between and regional size. δ 9 USE OF INTERMEDIATE INPUTS All LQ-based methods assume identical regional and national technology, i.e. that national and regional firms use the same proportions of different inputs to produce a given commodity. Unfortunately, this assumption cannot be tested directly with the data available here because each sector’s imports from other regions are not disaggregated by type of input. Instead, we shall test the assumption that Córdoba and Argentina use the same mix of intermediate and primary inputs. Primary inputs include value added and imports from abroad. Value added refers to the income of capital and labour. The following regression was formulated to test the hypothesis that Córdoba and Argentina used the same mix of intermediate and primary inputs in 2003: (29) Ijr = + + α βIjn εjr where is a survey-based estimate of the proportion of intermediate inputs (including inputs Ijr imported from other Argentinian regions) used by sector in Córdoba, is the j Ijn corresponding proportion of intermediate inputs for Argentina, and is a random error term. εjr The following result was obtained (n = 28): (30) Standard errors: 0.0508 0.1188 = 0.595. R2 This regression gives some grounds for rejecting the null hypotheses = 0 and = 1; in α β
wished to use the AFLQ rather than the FLQ, then a slightly higher value of δ would need to be chosen at the outset. It is evident that both approaches reviewed here have merits and demerits, which should be borne in mind when deciding which one to pursue. One should also be aware that, with Bonfiglio’s method, the estimated δ declines with regional size, whereas Flegg and Tohmo’s method exhibits a positive relationship between δ and regional size. 9 USE OF INTERMEDIATE INPUTS All LQ-based methods assume identical regional and national technology, i.e. that national and regional firms use the same proportions of different inputs to produce a given commodity. Unfortunately, this assumption cannot be tested directly with the data available here because each sector’s imports from other regions are not disaggregated by type of input. Instead, we shall test the assumption that Córdoba and Argentina use the same mix of intermediate and primary inputs. Primary inputs include value added and imports from abroad. Value added refers to the income of capital and labour. The following regression was formulated to test the hypothesis that Córdoba and Argentina used the same mix of intermediate and primary inputs in 2003: Ijr = α + βIjn + εjr (29) where Ijr is a survey-based estimate of the proportion of intermediate inputs (including inputs imported from other Argentinian regions) used by sector j in Córdoba, Ijn is the corresponding proportion of intermediate inputs for Argentina, and εjr is a random error term. The following result was obtained (n = 28): (30) Standard errors: 0.0508 0.1188 R2 = 0.595. This regression gives some grounds for rejecting the null hypotheses α = 0 and β = 1; in
2004_20150531101_CordobaMexicoconferencepaper.docx