'Fair Trade' Coffee and the Mitigation of Local Oligopsony Power

In recent years there has been considerable growth in ‘Fair Trade’ markets for several commodities, but most notably for coffee. We argue that coffee is grown under conditions that might well subject growers to the market power of intermediaries. Using an approach designed to evaluate the impact of state trading enterprises, we develop an oligopsony model of intermediaries. In this model, ‘Fair Trade’ firms optimize a welfare function that includes the producer surplus of growers. This concern for growers’ welfare among some intermediary firms helps to alleviate the market power distortion. We calibrate the model to price data reported by a fair trade organization, and consider the counterfactual removal of fair trade behavior by intermediaries and customers downstream. As expected, the income of coffee growers (in aggregate) is reduced, though the effects are quite small.coffee, fair trade, oligopsony

The Income and Consumption Effects of Covid-19 and the Role of Public Policy

We provide empirical evidence on the labour market impacts of COVID-19 in the UK and assess the effectiveness of mitigation policies. We estimate the relationship between employment outcomes and occupational and industrial characteristics and assess the effects on consumption. Seventy per cent of households in the bottom fifth of the earnings distribution hold insufficient assets to maintain current spending for more than one week. We compare the effectiveness of the UK's Coronavirus Job Retention Scheme and of Economic Impact Payments in the US. The EIPs are more effective at mitigating consumption reductions as they have full coverage, depend on household structure and are higher for low-income workers

On Covid-19: new implications of job task requirements and spouse's occupational sorting

The Covid-19 pandemic has disrupted working life in many ways, the negative consequences of which may be distributed unevenly under lockdown regulations. In this paper, we construct a new set of pandemic-related indices from the Occupational Information Network (O*NET) using factor analysis. The indices capture two key dimensions of job task requirements: (i) the extent to which jobs can be adaptable to work from home; and (ii) the degree of infection risk at workplace. The interaction of these two dimensions help identify which groups of workers are more vulnerable to income losses, and which groups of occupations pose more risk to public health. This information is crucial for both designing appropriate supporting programs and finding a strategy to reopen the economy while controlling the spread of the virus. In our application, we map the indices to the labor force survey of a developing country, Thailand, to analyze these new labor market risks. We document differences in job characteristics across income groups, at both individual and household levels. First, low income individuals tend to work in occupations that require less physical interaction (lower risk of infection) but are less adaptable to work from home (higher risk of income/job loss) than high income people. Second, the positive occupational sorting among low-income couples amplifies these differences at the household level. Consequently, low-income families tend to face a disproportionately larger risk of income/job loss from lockdown measures. In addition, the different exposure to infection and income risks between income groups can play an important role in shaping up the timing and optimal strategies to unlock the economy