Industrial Clusters and Micro and Small Enterprises in Africa: From Survival to Growth

Page 121

Location, Market Access, and Business Performance of Cluster-Based Enterprises

Table 5.4

99

Determinants of Performance in the Arusha Furniture Cluster

Variable Age of owner Age of owner, squared Previous furniture sales Furniture maker before (dummy) Manager’s primary school education Production training % of own ethnicity Years of experience of skilled worker Years in operation Amount of production of each enterprise Equipment Amount of production in the subcluster Wood-processing waiting time Density Number of observations R2

Total efficiency

Technical efficiency

Allocative efficiency

0.03 (0.65) 0.00 (–0.60) –0.08** (–2.09) –0.04* (–1.93) 0.01 (–0.58) 0.0003 (0.03) –0.05 (–1.50) –0.001 (–0.81) –0.004** (–2.28) 0.063*** (5.33) –0.01 (–0.46) 0.013 (0.72) –0.003** (–2.41) –0.002 (–1.57) 215 0.37

–0.01 (–0.93) 0.00 (1.18) –0.07* (–1.66) –0.05* (–1.68) 0.02 0.79) 0.0008 (–0.05) –0.035 (–0.93) –0.003** (–2.11) –0.06*** (–3.14) 0.095*** (8.23) 0.02 (0.65) 0.029 (1.34) –0.002 (1.60)– –0.001 (–0.93) 215 0.52

0.00 (0.01) 0.00 (–0.56) –0.16** (–2.25) 0.06 (0.97) –0.1** (–1.97) –0.023 (–0.65) –0.006 (–0.07) 0.005* (1.86) 0.001 (0.24) –0.01 (–0.63) –0.01 (–0.63) –0.01 (–0.16) 0.04 (0.89) –0.13*** (–2.94) 215 0.15

Quality: dryness of wood 0.024 (0.97) 0.00 (–0.89) 0.24** (2.20) 0.12** (2.08) 0.07 (1.56) 0.08 (1.55) 0.07 (0.58) –0.005 (–1.41) –0.006 (–0.64) 0.01 (0.46) 0.09* (1.73) –0.08 (–1.10) –0.02* (–1.87) 0.0003 (0.06) 219 0.1

Source: Muto, Chung, and Shimokoshi 2009. Note: Robust z statistics are in parentheses. *** p < 0.01. ** p < 0.05. * p < 0.10.

products, is influenced more by the geographic condition for value chain linkages. Wood-processing waiting time is negatively associated with allocative efficiency and product quality. This suggests that upstream supporting activity in the value chain of furniture production is crucial to the performance of furniture workshops in Arusha Municipality. While


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