Measuring the influence of networks on transaction costs using a non-parametric regression technique
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Measuring the influence of networks on transaction costs using a non-parametric regression technique. / Henningsen, Géraldine; Henningsen, Arne; Henning, Christian H.C.A.
Frederiksberg : Department of Food and Resource Economics, University of Copenhagen, 2013.Research output: Working paper
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TY - UNPB
T1 - Measuring the influence of networks on transaction costs using a non-parametric regression technique
AU - Henningsen, Géraldine
AU - Henningsen, Arne
AU - Henning, Christian H.C.A.
PY - 2013
Y1 - 2013
N2 - All business transactions as well as achieving innovations take up resources, subsumed under the concept of transaction costs. One of the major factors in transaction costs theory is information. Firm networks can catalyse the interpersonal information exchange and hence, increase the access to non-public information so that transaction costs are reduced. Many resources that are sacrificed for transaction costs are inputs that also enter the technical production process. As most production data do not distinguish between these two usages of inputs, high transaction costs result in reduced observed productivity. We empirically analyse the effect of networks on productivity using a cross-validated local linear non-parametric regression technique and a data set of 384 farms in Poland. Our empirical study generally supports our hypothesis that networks affect productivity. Large and dense trading networks and dense information networks and household networks have a positive impact on a farm’s productivity. A bootstrapping procedure confirms that this result is statistically significant.
AB - All business transactions as well as achieving innovations take up resources, subsumed under the concept of transaction costs. One of the major factors in transaction costs theory is information. Firm networks can catalyse the interpersonal information exchange and hence, increase the access to non-public information so that transaction costs are reduced. Many resources that are sacrificed for transaction costs are inputs that also enter the technical production process. As most production data do not distinguish between these two usages of inputs, high transaction costs result in reduced observed productivity. We empirically analyse the effect of networks on productivity using a cross-validated local linear non-parametric regression technique and a data set of 384 farms in Poland. Our empirical study generally supports our hypothesis that networks affect productivity. Large and dense trading networks and dense information networks and household networks have a positive impact on a farm’s productivity. A bootstrapping procedure confirms that this result is statistically significant.
M3 - Working paper
T3 - IFRO Working Paper
BT - Measuring the influence of networks on transaction costs using a non-parametric regression technique
PB - Department of Food and Resource Economics, University of Copenhagen
CY - Frederiksberg
ER -
ID: 46952038