*4.4.2. Risk management strategies*

Table 8 summarizes the multiple regression models of the risk management strategy components and the socioeconomic variables for all farmers. The goodness-of-fit coefficients of all models were rather low, except for model three where the coefficient explained around 27 per cent of the variation of the dependent variable. Models 1-4 are statistically significant (P< 0.01).The age variable is insignificant in relation to the risk strategy components of all farmers.

Sources of Risk and Risk Management Strategies: The Case of Smallholder Farmers in a Developing Economy 469

*AR1 AR2 AR3 AR4* 


0.023 -0.275\*\*\* 0.054 0.158\*\*

0.002 0.026 -0.001



0.092 -0.160\*\*

that farmers in the north-east region perceived these risk strategies as more important than

the central region farmers. This is because most north-east farmers are poorer.

*Independent variables Risk strategy components b*

Gender d -0.019 -0.107 -0.136\*

Net farm income -1.11E-06\*\*\* -1.98E-06\*\*\* -7.67E-07\*

Farm location h -0.383\*\*\* -0.143\*

Finance farm business i

c

e

f

i

j

Annual household income j

a Variables and models significant at \*

d 1, if farmer is male, 0 if female;

Source: Field survey, 2009

income and AR4=financial management;

Household size 0.033\*

1, if the farmer's age over 40 years old, 0 otherwise;

 1, if the farming experience over 30 years, 0 otherwise; g 1, if the farmer has off-farm work, 0 if no off-farm work;

characteristics of all sampled Thai farmers (n=800) a

1, if farm has a loan, 0 if farm without a loan; and

**5. Implication of the results** 

Constant 3.310\*\*\* 2.956\*\*\* 2.523\*\*\* 3.428\*\*\* Age c 0.054 0.124 0.003 -0.002

Highest education e 0.258\*\*\* 0.167\*\* 0.378\*\*\* 0.110 Farming experiences f -0.132\*\* -0.238\*\*\* -0.100 -0.121\* Off-farm work g 0.249\*\*\* 0.227\*\*\* 0.944\*\*\* 0.150\*\* Farm size 0.001 0.015\*\*\* 0.003 -0.004

*R2* 0.146\*\*\* 0.138\*\*\* 0.267\*\*\* 0.053\*\*\*

b Factors AR1-4 are labelled as AR1=farm production and marketing management, AR2=diversification, AR3=off-farm

Farmers in both regions perceived 'unexpected variability of input prices' as the most important sources of risk on the farm. In addition to the prices of chemical fertilizer, the increase in wage rates and higher land rental rates are the main factors that pushed the farm production costs upward. Over the past decade, the intervention of the Thai government in agricultural input policies had actually declined. The distribution of chemical fertilizers at reduced cost was the only scheme that the government organized to assist poor rural farmers. However, this scheme has recently been terminated due to limited government budget and

this consequently reduced opportunities for the farmers to control production costs.

*P*<0.1, \*\**P*<0.05 and \*\*\**P*<0.01;

1, if the highest education of the farmer is high school and higher, 0 if primary school education or less;

**Table 8.** Multivariate regression of the risk strategy components and household and farm

h 1, if the farmer's farm is located in central region, 0 if a farm located in north-east region;

1, if household income greater than 90,001 baht and 0 represent otherwise.

Gender was negatively related to 'off-farm income', which means that female household heads perceived this risk strategy as more important than male household heads. The reason is because the female farmers or wives can easily find off-farm work, such as weaving and/or handicrafts that are widely found throughout the north-east region, to supplement their household income.

The highest educational level was positively related to the 'farm production and marketing management', 'diversification' and 'off-farm income' risk strategies. This implies that the more educated farmers perceived these risk management strategies as highly important. This finding is similar to that of Mustafa who argued that the more educated farmers performed better in managing their farm business compared with less educated farmers.(30)

The length of farming experience was negatively related to the 'farm production and marketing management', 'diversification' and 'financial management' risk strategies. This suggests that less experienced farmers were more likely to be interested in employing these strategies to manage risk on their farms than the more experienced farmers.

Off-farm work was positively related to all four risk strategy components. These relationships may be due to the farmers who have off-farm work to enhance their farm income; they are willing to adopt such strategies to improve and maintain their farm income. Similarly, the net farm income coefficient shows a negative relationship with all four risk strategy components. This suggests that the farmers who have a lower net farm income believe that these risk strategies can help to increase their farm income.

Farm size was positively related to the 'diversification' strategy. Farmers with larger farms perceived a diversification strategy as highly important. It should be noted that farm size is one of the constraints to diversification, that is, farmers with a small holding have limited ability to diversify their farm activities.(33)

Farmers who had higher annual household incomes perceived the 'financial management' strategy as highly important. In contrast, they perceived the 'diversification' strategy as less important than farmers who had lower annual income. In addition, risk management strategies related to 'farm production and marketing management' and 'off-farm income' were perceived as less important by the farmers who had loans. Farmers with larger households perceived 'farm production and marketing management' as slightly more important than smaller household farmers.

The farm location coefficient was negatively related to 'farm production and marketing management', 'diversification' and 'financial management' risk strategies. This may imply that farmers in the north-east region perceived these risk strategies as more important than the central region farmers. This is because most north-east farmers are poorer.


a Variables and models significant at \* *P*<0.1, \*\**P*<0.05 and \*\*\**P*<0.01;

b Factors AR1-4 are labelled as AR1=farm production and marketing management, AR2=diversification, AR3=off-farm income and AR4=financial management;

c 1, if the farmer's age over 40 years old, 0 otherwise;

d 1, if farmer is male, 0 if female;

468 Risk Management – Current Issues and Challenges

*4.4.2. Risk management strategies* 

components of all farmers.

supplement their household income.

ability to diversify their farm activities.(33)

important than smaller household farmers.

Table 8 summarizes the multiple regression models of the risk management strategy components and the socioeconomic variables for all farmers. The goodness-of-fit coefficients of all models were rather low, except for model three where the coefficient explained around 27 per cent of the variation of the dependent variable. Models 1-4 are statistically significant (P< 0.01).The age variable is insignificant in relation to the risk strategy

Gender was negatively related to 'off-farm income', which means that female household heads perceived this risk strategy as more important than male household heads. The reason is because the female farmers or wives can easily find off-farm work, such as weaving and/or handicrafts that are widely found throughout the north-east region, to

The highest educational level was positively related to the 'farm production and marketing management', 'diversification' and 'off-farm income' risk strategies. This implies that the more educated farmers perceived these risk management strategies as highly important. This finding is similar to that of Mustafa who argued that the more educated farmers performed better in managing their farm business compared with less educated farmers.(30) The length of farming experience was negatively related to the 'farm production and marketing management', 'diversification' and 'financial management' risk strategies. This suggests that less experienced farmers were more likely to be interested in employing these

Off-farm work was positively related to all four risk strategy components. These relationships may be due to the farmers who have off-farm work to enhance their farm income; they are willing to adopt such strategies to improve and maintain their farm income. Similarly, the net farm income coefficient shows a negative relationship with all four risk strategy components. This suggests that the farmers who have a lower net farm

Farm size was positively related to the 'diversification' strategy. Farmers with larger farms perceived a diversification strategy as highly important. It should be noted that farm size is one of the constraints to diversification, that is, farmers with a small holding have limited

Farmers who had higher annual household incomes perceived the 'financial management' strategy as highly important. In contrast, they perceived the 'diversification' strategy as less important than farmers who had lower annual income. In addition, risk management strategies related to 'farm production and marketing management' and 'off-farm income' were perceived as less important by the farmers who had loans. Farmers with larger households perceived 'farm production and marketing management' as slightly more

The farm location coefficient was negatively related to 'farm production and marketing management', 'diversification' and 'financial management' risk strategies. This may imply

strategies to manage risk on their farms than the more experienced farmers.

income believe that these risk strategies can help to increase their farm income.

e 1, if the highest education of the farmer is high school and higher, 0 if primary school education or less;

f 1, if the farming experience over 30 years, 0 otherwise;

g 1, if the farmer has off-farm work, 0 if no off-farm work;

h 1, if the farmer's farm is located in central region, 0 if a farm located in north-east region;

i 1, if farm has a loan, 0 if farm without a loan; and

j 1, if household income greater than 90,001 baht and 0 represent otherwise.

Source: Field survey, 2009

**Table 8.** Multivariate regression of the risk strategy components and household and farm characteristics of all sampled Thai farmers (n=800) a
