Yam is the sole crop that performs very well on a forest land or ondense wooded savanna newly converted to agriculture. Thus, the farmer starts the farm by cropping yam in the first year. The other food crops , and the cash crops, are cultivated either in the second, third,or forth year after the land is set to farm. For these reasons, the land area allocated annually for yam planting has constituted the proxy in this study of deforestation.Another consideration is that the vegetation includes both the wooded savanna and the forest and because these two vegetation cover types may coexist in the region, as largely discussed above, the land conversion to agriculture may include also the wooded savanna. At the national level and according the 2011 Agriculture census , the population in agriculture in rural area is of 97.3% in average.
The farms of 0.5 ha in size represent 76%, 0.5 1 ha18%, 1 2 ha 5%, and finally, the farms of more than 10 ha, 1%.The variables data or the proxies necessary for the study were collected in panel for the time period from 1995 to 2015, and from the prefectures in the Central region of Togo. There are four prefectures retained for the study which are Blitta, Sotouboua, Tchamba, and Tchaoudjo. The fifth prefecture, the Plain of the Mo River, is newly created and there are no data available for the whole study time period. These data are mainly the forest data, agricultural food crop data, the cash crop data, and the socio-economic data.The forest data are secondary data compiled in a monthly basis by the prefectures.The annual reports which constitute the major sources of the data collection are normally available either in the Regional Forest Office in Sokode, vertical farming racks or at the General Secretary of the Ministry in charge of the environmental and forest resources. The variables of interest here are the wood biomass which may be categorized as fuel wood, charcoal and industrial wood production. Data on the receipts collected from various forestry activities including transport permit,cutting certificates, and also from the fines for illegal forestry operations, are available in these annual reports.
Data on crop production are also secondary data made available in most cases by the Office of Agriculture Statistics, Information and Documentation of the Ministry of Agriculture. These data are the results of periodical agricultural census. But each year the census data are updated to make available data in the yearly basis. The variables considered here are the production and the out putprices, the fertilizer quantity and price, and the pesticide quantity and price for each year. As announced above, the concerned food crops are cereals, tuber and pulses. The major important cash crop produced in the Region is the cotton, but coffee and cocoa are also cultivated under the dense forests in Blitta, the prefecture at the south most of the region. The historical data were made available for this study by New Office of Cotton Society , formally called SOTOCO. The data include the cotton production, the price, cotton pesticides used, cotton fertilizer used and their prices. The socio-economic data are provided either by the National Institute of Statistics,and Economics and Demographic Studies , or from the websites.Besides the panel data, single point data such as data on agriculture systems were obtained by question and answer with the Institute of Counseling and Support ’s agents and with individual farmer producers implicated in major crops and cotton production.
This information concerns the recent years from 2011 to 2016. The common farming practice in the area is the mix cropping, and yam is the crop that starts the rotation. Therefore we decide the annual area converted toy am planting constitutes the proxy for the vegetation loss. The analysis results are compiled in Table 2 the full model, where are reported the 20 independence variables included in the model, their Fixed models and First Difference coefficient estimates, and the resulting probabilities. We are not able to report the reduced model outputs , the national cotton pesticide cost, the national cotton price and the national minimum wage, because these independent variables do not quite explain by themselves the vegetation cover area loss .Furthermore, including the time dummy’s to capture the time effect results in the drop of eight variable coefficients from the model, and significant statistical effect for all the fifteen non-dropped independent variables. Even though the pFtest for individual time effect is significant , we are not able to provide a Robust Standard Error of the time fixed effect for the full model either. A bunch of variable coefficients are also dropped from the model.