estate are almost nonexistent in rural areas and account for 1%-3% of urban jobs, which are most commonly administrative in nature. Finally, the general services category is the most important, accounting for 40%-50% of urban jobs across all countries, and 15%-30% of rural jobs in Ethiopia and Malawi and 25% in Tanzania and Uganda. These wage workers include teachers, health, social and religious workers, public administrators, technicians, domestic service providers, as well as restaurant, hotel, and tourism employees. General services account for a smaller share of firms than of employment. The firms typically involve restaurants and caterers, bars, hotels, professional service providers, and repair shops.

Buying and selling agricultural products comprises a large share of commerce NFE activity and wage employment. As with the industry sector, the services sector activities in which rural households participate are non-tradable in nature, and very focused on local consumers. Because these service-sector activities serve local consumers whose incomes are dominated by agriculture-sector activities, the Mellor-Johnston linkages are again quite prominent. One would expect agricultural productivity growth to spur demand for increased local service sector labor. Given the nature of service sector activities, one would not expect to see strong growth in the services sector absent agricultural growth.

# **5. Robustness of productivity gap measurement**

Sector productivity gap estimates are sensitive to prospective measurement error of firm revenue and wage earnings. Consumption can be thought of as household profits after participation costs (for wage labor) and production costs (for firms), assuming no savings or dissavings. Because households who face stochastic income generally smooth their consumption from year to year, consumption can be a good measure of permanent income (Bhalla 1978). It is a central focus of LSMS-ISA surveys to generate consumption aggregates, so this variable plays to the strengths of the data. Consumption aggregates are generated by each country’s statistics office and released with the datasets. They include cash expenditures as well as the imputed value of items that are produced and consumed by the household, such as agricultural goods. The consumption gap estimates are a ratio in per capita consumption between households participating primarily in agriculture and those participating primarily in industry and services, respectively (Figure 10).

These gaps are fairly similar across countries, and are considerably smaller than productivity gaps, though they follow similar rankings. Households primarily in the industry sector consume 1.2-3 times more per capita per year than agricultural households. Households primarily in the services sector consume 1.5-4 times more per capita per year than agricultural households. The consumption gaps are quite similar in magnitude to the per-person-per-year productivity gaps. They are slightly larger in Ethiopia and Malawi, and smaller in Tanzania and Uganda. As with productivity gaps, consumption gaps also disappear almost entirely when they are expressed per hour of labor supplied by each household. This suggests that differences in consumption across sectors (as with differences in returns to sector participation) can be explained in large part by differences in hours worked across sectors.

Because labor supply variables for different activities are constructed from different types of survey questions, there is concern that differences in labor supply across activities could arise from different survey recall approaches rather than actual labor supply differences. To address this concern, I construct an alternate set of labor supply variables using only 7-day recall 14