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218

A further example of data volatility can be seen by examining the number of reported farming
households.
In contrast to the commercial farms sector where the number of farming households is
reported to fluctuate around a mean of 3,000, significant changes in the number of reported
noncommercial farming households appears in the CSO data. From a high near 1.3 million in the early
1970s, the number of households drops to around 1 million for an extended period, until increasing
again to near 1.2 million in the mid-1980s (see table 7.11). Fluctuations of 300,000 households in the
farming population (plausibly 1 million or more individuals) is difficult to explain except perhaps as
a general problem with the data collection system.

Table 7.11: Number of noncommercial farm households

Year

Copperbelt/
Northwestern

Central/

Southern/

Lusaka

Northern/
Luapula

Eastern

Western

All

1971

144,400

273,000

499,600

230,400

148,600

1,296,000

1972

146,400

239,500

488,100

209,000

191,600

1,274,600

1973

97,600

203,300

348,100

273,200

109,000

1,031,200

1974

95,700

232,900

381,900

192,600

158,000

1,061,100

1975

111,800

247,400

318,600

128,500

157,500

963,800

1976

129,700

197,800

372,900

222,600

148,600

1,071,600

1982

124,200

180,580

320,890

208,350

151,900

985,920

1983

124,880

172,710

320,760

222,890

133,600

974,840

1984

135,970

183,360

318,120

247,350

152,120

1,036,920

1985

111,328

260,201

343,651

256,627

189,130

1,160,937

Source: Derived from Zambia CSO data.

VI. Revenues and expenditures

The CSO also provides data on farm expenditures and revenues. Tables 7.12-7.15 present
results for the two broad regions of commercial farms defined above, excluding data on farm livestock
revenue. They suggest a dramatic nominal increase in the kwatcha value of operations in the late
1980s, on both the revenue and the expenditure side, which corresponds to a period of hyperinflation.
When nominal values are deflated by a low-income CPI, farm sales and operating expenses for all
farm categories are shown to increase in real terms as well, although wide fluctuations are evident.
Results are not substantially different if the high-income CPI is used as a deflator. The rather
astounding 1989 increase in operating expenses (fertilizer and pesticide applications, machinery, seed,
etc.) in the Central, Southern, and Lusaka combined provinces on medium-sized farms cannot readily
be explained.



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