The estimates in table 7 provide a clear picture. In a sub-sample of teams consisting of workers from two different tribes categorized as belonging to the same tribal bloc, little if any discrimination against non-coethnic processors occurs. The output of vertically mixed teams is for example not significantly different from that of homogeneous teams in the Luo – Luhya sub-sample. But within two different sub-samples of teams consisting of workers of two specific tribes categorized as belonging to different tribal blocs here, discrimination is pervasive and of an extent similar to that seen in the full-sample analysis in table 4. There are only minor differences across the Kikuyu – Luo and the Kikuyu – Luhya sub-samples, analyzed in columns 1 – 2 and 3 – 4 of table 7 respectively. So far we have seen strong evidence indicating that team-level ethnic diversity lowers productivity in the context of factory production in Kenya. If diversity effects are driven by discriminatory preferences, then we would expect the negative effect of ethnic diversity on private sector output to vary with factors that influence taste for discrimination, such as the political climate and relations between groups. A shift in taste for discrimination should differentially lower the output of mixed teams. In the next sub-section, I analyze differences in output between homogeneous and mixed teams during the period of ethnically-based, political conflict in Kenya in early 2008.The two coalitions in Kenya’s December 27 2007 presidential election were ethnically based. In advance of the election, grow lights for cannabis opinion polls predicted that the coalition led by Luo challenger Raila Odinga would oust the sitting Kikuyu- led coalition represented by incumbent president Mwai Kibaki. But results were delayed and the Kibaki victory announced on December 29 disputed by the opposition and the international community.
Widespread violence against Kikuyu and Kikuyu- allied tribes erupted, and counter-attacks soon followed. More than 1,200 people were killed and 500,000 displaced in the months that followed . On February 28, a peace agreement was reached, though violence continued in many areas, and it was not until after April 3 when the two sides reached an agreement on the composition of a power-sharing government that the political crisis ebbed. The conflict period significantly disrupted life in parts of Kenya. However, plant supervisors reported that logistics and worker absence at the farm was largely unaffected and that production continued as usual. Because the workers live on the farm in a gated community it was safest to remain on the farm. If the plant’s ability to operate was nevertheless affected, a decrease in productivity, as measured by the econometrician, should be observed in all teams. The model predicts an increase in the gap between the average output of homogeneous and mixed teams if attitudes towards workers of the other ethnic group worsened when conflict began. I interpret a possible increase in taste for discrimination as a decrease in the weight attached to the well-being of non-coethnics. In table 8, the difference in output between mixed and homogeneous teams before and after conflict began is compared. Data from 2007 and the first six weeks of 2008 is used. There was no significant change in the output of homogeneous teams when conflict began. If suppliers have social preferences, the impact of conflict on the productivity of homogeneous teams will reflect a combination of two factors. First, farm-wide disruption effects may have negatively affected output in all teams. Second, it is possible that conflict led to an increase in workers’ weight on the utility of coethnics: the findings of Eifert, Miguel, and Posner suggest that Africans increasingly identify with coethnics during times of heightened political competition between groups. I cannot rule out general disruption effects or an increase in the utility workers derive from coethnics’ output and income. But the combination of supervisors’ reports and a conflict coefficient for homogeneous teams that is essentially precisely zero points to little farm-wide disruption effects and little effect on workers’ weight on coethnics’ utility.
The output gap between homogeneous and vertically mixed teams nearly doubled in early 2008. Output in vertically mixed teams decreased by seven percent when conflict began. The results in table 8 thus indicate that upstream workers undersupply non-coethnic downstream workers to a significantly greater extent during times of ethnic conflict, as predicted by the model if taste for discrimination increased. Output in horizontally mixed teams decreased by four percent when conflict began, but there was a small but significant increase in the output of coethnic processors in horizontally mixed teams. An increase in upstream discrimination against workers of other ethnic groups thus appears to increase the supply of flowers to those downstream workers who belong to the same ethnic group as suppliers, as predicted by the model. The relative benefits of flowers supplied to coethnic processors in horizontally mixed teams go up if conflict lowers the utility upstream workers derive from non-coethnics’ output, even if suppliers’ weight on coethnics’ utility is unaffected. In light of the model presented above, the results for the conflict period thus suggest that discriminatory attitudes towards co-workers of other ethnic groups worsened in Kenya in early 2008. It appears that the economic costs of ethnic diversity vary with the political environment. A back-of-the-envelope calculation suggests that the increase in supplier discrimination during conflict may have cost the farm as much as US$560,000 in profit per year, had it not responded. Firms may be forced to take measures to limit distortions that arise from internal, ethnic discrimination, especially in times of conflict. In the next sub- section, I analyze how the gap in output between homogeneous and mixed teams was affected when the plant six weeks into the conflict period changed the pay system for processors and thereby altered the incentives facted by biased upstream workers.On February 11 2008, the farm began paying processors w per rose finalized by the team, rather than 2w per rose finalized by the processor herself as before.
As in standard incentive models, the framework above predicts that processors will freeride on each others’ effort when paid in part based on the output of the other processor. Free riding should negatively affect output in all teams, but in horizontally mixed teams an offsetting positive effect is expected. Under team pay, suppliers are unable to influence the relative pay of the two processors through relative supply. If the higher output for processors of the supplier’s ethnic group observed under individual pay is driven by suppliers’ taste for discrimination, indoor cannabis grow system a decrease in the output gap between coethnic and non-coethnic processors in horizontally mixed teams is thus expected when team pay is introduced. To test these predictions, I consider the period after processors’ pay system was changed and through the remainder of 2008 as a single team pay period. Figure 8 displays team and individual output during the three sample periods: pre-conflict , conflict , and the team pay period . The decrease in output in mixed teams during conflict is apparent. Comparing the second and third periods, the figure also clearly indicates that the introduction of team pay had a positive effect on output in horizontally mixed teams.Corresponding regression results are in table 9. The results indicate that team pay leads to some degree of free riding among processors: output in homogeneous and vertically mixed teams is 1 percent lower under team pay. The modest magnitude of this effect is noteworthy and interesting in itself. Output in horizontally mixed teams is four percent higher under team pay, as seen in columns 3-4 and 7-8 in table 9. The difference in output between horizontally mixed and homogeneous teams thus decreased significantly when team pay was introduced. The introduction of team pay essentially canceled out the effect of conflict on output in horizontally mixed teams, returning the difference in output between homogeneous and horizontally mixed teams to pre-conflict levels. The increase in horizontally mixed teams’ output appears to be due to horizontal favoritism being eliminated when biased suppliers’ ability to increase the relative income of favored processors through relative supply was removed, as predicted by the model. There is no statistically significant difference in the output of the coethnic processor and the non-coethnic processor in horizontally mixed teams during the last ten and a half months of 2008. An output gap of 32 percent between processors of the supplier’s ethnicity and processors who are not of the supplier’s ethnicity in horizontally mixed teams was eliminated by the introduction of team pay. The positive impact on output in horizontally mixed teams, which make up half of all teams, led to an overall increase in output when team pay was introduced. However, output in horizontally mixed teams remains lower than in homogeneous teams under team pay, and output in vertically mixed teams still lower. Under team pay a biased supplier continues to derive greater benefit from flowers supplied the more downstream workers belong to her tribe. The ranking of output of teams of different ethnicity configurations observed under team pay is thus due to incentives for vertical discrimination remaining in place, it appears. The model presented above, in which the productivity effect of ethnic diversity in teams arises from a taste for discrimination on the part of upstream workers, thus predicts the output response to the introduction of team pay well. Approximately one fourth of the yearly expected profit loss due to the impact of conflict on misallocation of flowers was avoided through the change in suppliers’ contractual incentives. It is difficult to imagine a standard economic model of joint production that would predict an increase in output when team pay is introduced.In the previous sub-section we saw that the economic costs of ethnic diversity vary with the political environment. The results in this sub-section suggest that, in high-cost environments, firms adopt “second best” policies to limit the distortions caused by ethnic favoritism. Group-based pay leads to free riding and reduces output in homogeneous teams, but the new pay system introduced by the plant during the conflict period in Kenya in early 2008 was likely designed to remove the ability of biased upstream workers to increase one processor’s pay relative to the other’s through differential allocation of flowers. Distortionary discrimination fell and the net effect was positive. Interestingly, La Ferrara also finds that ethnically diverse cooperatives in Nairobi are more likely to adopt group-pay. It thus appears that ethnic diversity has an important influence on how firms organize production in the private sector.Note first that informational and technological diversity effects are unlikely to explain this paper’s results. Suppose that the higher output observed in homogeneous teams during the pre-conflict, individual pay period was due to inferior technology or information in diverse teams. In that case it is difficult to see why output in mixed teams would fall differentially during conflict, and why the output of the two processors in horizontally mixed teams would be equalized under team pay. Cooperational effects have proven difficult to distinguish from social preferences , in part because such theories typically have few testable implications. Some forms of cooperational diversity effects could explain the observed decrease in mixed teams’ output during conflict. If trust for example facilitates cooperation, an erosion of trust between workers of different ethnic groups during times of ethnic antagonism could lead to a decrease in mixed teams’ output. Other forms of cooperational diversity effects could explain the observed increase in the output of non-coethnic processors in horizontally mixed teams under team pay. Coethnic processors that can exert effective social pressure on the upstream worker may for example induce the supplier to supply more to non-coethnic processors in horizontally mixed teams under team pay because processors derive benefits from the output of the other processor under team pay. It is, however, difficult to think of cooperational or other forms of non-taste-based ethnic diversity effects that can simultaneously explain a decrease in mixed teams’ output during conflict, equalization of processors’ output in horizontally mixed teams when team pay is introduced, and the other results seen in this paper. Though I cannot rule out that other forms of ethnic diversity effects also play a role, I thus conclude that the leading explanation for the lower output observed in ethnically diverse teams at the plant is taste-based discrimination on the part of suppliers.