1. Many transition economies also have a relatively small share of the population in the agricultural sector so rising output will not lead directly to higher incomes for much of the population.

2. Official data on labour use in transition agriculture are prone to measurement errors and statistical problems and should be interpreted with care. Different data sources often provide different numbers and do not always distinguish between full-time and part-time employment. Hence, in those countries in which more part-time work is being done, but which continue to report all producers involved in agricultural production as full-time labour units, labour productivity trends will be understated. Also, the aggregate data hide important other reallocations of labour. For example, while overall labour use in agriculture in China rose slightly during the first five years after reform (10 per cent), major efficiency gains in cropping occurred from the reallocation of labour from crops to livestock production and other sideline activities (e.g. various self-employed enterprises—Lardy 1983; Fan 1991; Jin et al. 2002). Also, in other transition countries official labour data hide important changes in effective labour input. For example, in some of the CIS countries where former collective and state farms have survived, labour is often underemployed and members of rural households are officially still employed on these farms, even though they often spend a considerable part of their time working on their own household plots and are engaged in a myriad of other sideline activities (Lerman, Csaki, and Feder 2004). In such countries, the effects of these misreportings are ambiguous and depend on whether or not the output produced on their own plots are included in output figures. If private plot output is included, we, in fact, will be measuring rising productivity when it is actually rising. If the output of these plots is not included in reported output, labour productivity measures will be underreported like those in countries in which agricultural labourers are shifting from full- to part-time farmers. We use data from the Asian Development Bank for Azerbaijan, Kazakhstan, Kyrgyzstan, Moldova, Tajikistan, Turkmenistan, and Uzbekistan because for most of these countries there are no consistent data in the database of the International Labour Organization for the full period.

3. A number of factors increased the size in terms of labourers of the agricultural sector in countries such as Romania, Armenia, and several Central Asian nations. Policy, demographic and macroeconomic pressures, and other factors contributed to the rise of agricultural labour use in many countries: for example, in countries where the agricultural sector worked as a buffer after a collapse of the industrial economy (e.g. Romania, Kyrgyzstan), and in fact absorbed labour from other sectors. As in Vietnam, rapid population growth also contributed partly to the labour inflow in several Muslim countries, such as Uzbekistan and Turkmenistan. Finally, other events also contributed to rising agricultural labour. For example, in Armenia a regional conflict disrupted critical imports and industrial production, and many people migrated to rural areas.

4. In Table 2.3, the only exception is Romania where strong increases in dairy yields more than offset declines in crop yields.

5. As we will explain in Chapter 5, the inconsistent results for Russia are probably due to differences in sampling and reflect variations in the performance of different farm structures with the countries. An update of the Lerman and Brooks (2001) calculations indicates that TFP increases in Russia and Ukraine are due mostly to increases after 1995, as TFP declined before then.

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