2007年-世界发展银行全球_An_Empirical_Economic_Assessment_of_Impacts_of_Climate_Change_on_Agriculture_in_Zambia_37页_1mb

Summary of "An Empirical Economic Assessment of Impacts of Climate Change on Agriculture in Zambia"

Core Content

This report presents an empirical economic assessment of the impacts of climate change on agriculture in Zambia, using the Ricardian method to evaluate how climate variables affect agricultural productivity. The study is part of a larger project funded by the Global Environment Facility (GEF) and the World Bank, aimed at understanding climate change effects and promoting adaptation strategies in African countries.

Main Points

1. Agriculture in Zambia

• Agriculture is a major economic sector, contributing 18–20% to Zambia's GDP and providing a livelihood for over 60% of the population.
• It employs two-thirds of the labor force and is dominated by small- and medium-scale farming.
• Maize is the main crop, accounting for over 70% of the cultivated area in the Southern, Central, and Eastern provinces.
• Wheat is a winter crop grown by large-scale commercial farmers using irrigation.
• The main cropping season runs from November to April, with crop production dependent on rainfall.
• The country is divided into three agro-ecological zones (Zone I, II, III), based on rainfall and soil type.

2. Climate Change in Zambia

• Temperature in Zambia has increased at a rate of 0.6°C per decade, which is ten times the global average.
• Rainfall has shown declining trends, especially in Zone I, with more than 10 years out of 14 (1990/91–2003/04) experiencing below normal rainfall.
• Droughts have become more frequent and severe, especially in Zone I, with major impacts on food security and agricultural productivity.
• Climate change is associated with increased frequency and intensity of extreme weather events, such as floods and droughts, which affect soil fertility, livestock, and crop yields.

3. Research Methodology

• The Ricardian method is used to assess the economic impact of climate change on agriculture by analyzing the net farm revenue per hectare.
• A multiple linear regression model is employed, using climate, hydrological, soil, and socio-economic variables as explanatory variables.
• The model includes quadratic terms to capture non-linear relationships between climate variables and net farm revenue.
• The response variable is net farm revenue per hectare (NR_h), calculated as:
  $$
  \mathrm{NR_h} = \frac{\left[ \sum_{i=1}^{n} P_i C_i - \left(\sum_{j=1}^{m} Y_j X_{ij}\right) \right]}{A_h}
  $$
  where:
  • $P_i$ = unit price of crop $i$
  • $C_i$ = quantity produced of crop $i$
  • $X_{ij}$ = quantity of input $j$ purchased for producing crop $i$
  • $Y_j$ = unit price of input $j$
  • $A_h$ = total area planted by household $h$

4. Data Sources

• Household data was collected from 1015 households across 30 districts using stratified multistage cluster sampling.
• Climate data was obtained from satellite sources (US Department of Defense) covering the period 1988–2004.
• Soil data was sourced from the FAO database, and hydrological data (runoff) was obtained from the University of Colorado.

5. Key Findings

• Most socio-economic variables are not statistically significant in the model.
• Climate variables and their quadratic terms are significant.
• Key climate impacts:
  • An increase in November–December mean temperature has a negative effect on net farm revenue.
  • A decrease in January–February mean rainfall also has a negative effect.
  • An increase in January–February mean temperature and mean annual runoff has a positive effect on net farm revenue.
• Non-linear relationships:
  • Net revenue has a U-shaped relationship with November–December temperature.
  • Net revenue has a hill-shaped relationship with January–February temperature, January–February wetness index, and mean annual runoff.

Conclusion and Recommendations

• Climate change poses a significant threat to agricultural sustainability and food security in Zambia.
• The economic consequences of climate change are most evident in rainfed agriculture, which is the dominant form of farming in the country.
• The Ricardian approach is useful for assessing the impact of climate variables on farm revenue, especially in countries with abundant free land.
• The study recommends adaptation policies to minimize the negative impacts of climate change on agriculture, such as promoting drought-tolerant crops like sorghum and improving access to agricultural inputs and credit for small-scale farmers.

Key Variables and Their Relationships

Summary Statistics

• The net farm revenue per hectare (nr1_3) has a mean value of US$1258.79.
• The sample mean for November–December temperature (tcom1) is 21.72°C, and the turning point (minimum revenue) is at 23.48°C.
• The sample mean for January–February temperature (tcom2) is 19.7°C, and the maximum revenue is achieved at 20.7°C.

References

• Basist, et al. (2001)
• CSO (1992, 2002a, b)
• FAO (2003)
• Hulme (1996)
• IwMI & University of Colorado (2003)
• Kurukulasuriya & Rosenthal (2003)
• MoA (2000)
• Muchinda (2001)
• Mendelsohn et al. (1994)
• Munalula et al. (1999)