Research Article

Determinants of Livestock Farm Household’s Welfare with Main Focus on Women’s Involvement in Livestock Production in Rural Areas of District Mardan Khyber Pakhtunkhwa, Pakistan

Neelum Andaleeb1*, Munir Khan1, Syed Attaullah Shah1 and Rahmat Ullah2

1University of Agriculture Peshawar, Khyber Pakhtunkhwa, Pakistan; 2Balochistan Agriculture College Quetta, Pakistan.

Received | April 19, 2018; Accepted | November 22, 2018; Published | January 15, 2019

*Correspondence | Neelum Andaleeb, University of Agriculture Peshawar, Khyber Pakhtunkhwa, Pakistan; Email: [email protected]

Citation | Andaleeb, N., M. Khan, S.A. Shah and R. Ullah. 2019. Determinants of livestock farm household’s welfare with main focus on women’s involvement in livestock production in rural areas of District Mardan Khyber Pakhtunkhwa, Pakistan. Sarhad Journal of Agriculture, 35(1): 43-47.

DOI | http://dx.doi.org/10.17582/journal.sja/2019/35.1.43.47

Keywords | Determinants, Multistage sampling, Ordered logit model, Production, Livestock

Introduction

According to (Hashmi et al., 2007) crops and livestock were the main source of income for rural household because it adds a share of 69 percent to their monthly income. Women are involved in livestock farming and contribute to their family income (Aujla and Hussain, 2015; Khan and Khan, 2015; Borkar et al., 2017). Increase involvement of women in livestock activities not only increased income from livestock operations but also helps to reduce poverty. A comparison of low and high income farmers revealed that besides crop production, maintaining livestock was the key to reduce poverty.

Livestock is a dependable source of food as well as steady income. Reasonably sized livestock operations provide employment opportunities in rural areas where such opportunities are scarce and support local and national economy. Successful livestock operations are a reliable source of foreign exchange. For low income farmers, livestock offer a number of benefits such as liquid cash, means of transportation, and organic matter for crops. Farmers utilize livestock to plough fields and use manure to improve soil fertility. Dried manure is used as a source of energy for burning to cook meals and keep warm. Farmers use milk and milk derived products from their livestock, eat their meat, and sell cow hides for cash are among many other benefits farmers take advantage of by maintaining a healthy livestock. Rural women participate in livestock management by performing tasks such as cutting fodder, cleaning barns, and milking. Such tasks are considered extra work for women besides other routine chores. (Garcia et al., 2003).

The affluence and development of a nation depends on the position and development of its females, as women not only represent nearly half of its population but also positively influence the expansion of remain half of the population. Women in rural areas play significant role in various farming activities in many countries of the world. Women perform approximately all types of tasks in agriculture and livestock sector in rural areas. They also face many constraints while performing these tasks because they are also having to perform regular household activities. In Pakistan, majority of population live in the rural areas where major source of income depends directly or indirectly on crop production and livestock management. Rural women in Pakistan are among the millions of landless small farmers (Zahoor et al., 2009).

The purpose of this study is to investigate determinants of welfare of livestock farm households with special reference to women’s participation in livestock farming.

Limited literature was available on livestock farming in district Mardan, a relatively detail baseline survey was carried out in Mardan, and the data was collected to find out and to investigate livestock farm household welfare from the sample data of 274 farmers.

Materials and Methods

Study area and sampling technique

A multistage sampling technique was used for selecting the sample. In the first stage two tehsils namely Mardan and Katlang of district Mardan were selected for having maximum number of livestock farms. Each tehsil was further divided into urban and rural union councils (UCs) and three rural UCs were randomly selected from each. In the final stage, households in each selected union council were divided into livestock farmers and others. Households from livestock farming were selected randomly. A total of 274 households were selected, and number of households from each union council was selected based on Yamane’s formula (Yamane, 1967).

Where;

S= Sample size; N= Total number of livestock farm households in selected UCs; e = Precision which is set at 6% (0.06).

Data collection

A well-designed questionnaire was used to collect data from the selected farmers using face to face interview. Efforts were made to keep it simple and explicable so as to capture all the essential information.

Data analysis

Determinants of livestock farm household’s welfare: To measure livestock household’s welfare and analyze the effect of different policy tools on household’s welfare, economists use utilitarian approach. Utilitarian approach uses indirect/ maximum utility function for measuring changes in household’s welfare/ satisfaction from the direct or indirect consumption of goods and services or changes in income (Nicholson and Snyder, 2012; Hal and Varian, 2005).

Any change in household’s income changes their welfare (measured with indirect/ maximum utility function v(P,Y). Mathematically.

∆U = v(PY1) – v(P, Y0)

Where;

∆U = change in household’s welfare; V = is the household’s indirect/ maximum utility function; Y0 = is the initial income level; Y1 = is the new income level; P = price vector for goods and services consumed by the household.

Welfare theory reports direct relationship between household’s welfare and their income level (Nicholson and Snyder, 2012; Hal and Varian, 2005). Any increase in household’s income leads to rise in their welfare. This positive relationship allows economists to use household’s income level as a proxy variable for their welfare (Slesnick and Daniel (1998)).

In this study income was taken as proxy variable of welfare status of the livestock farm household. Livestock are known to play important role in the welfare of rural families by providing food, income, and materials to use as bio fuel. Based on poverty line, used by the United Nation and the World Bank, livestock farm households were divided into the following four categories.

Following studies conducted by Samman and Santos (2013) and Geda et al. (2005) an ordered logistic regression model was used to identify important determinants of livestock farm household’s welfare. Income categories were used as dependent variable to investigate the effect of the following important explanatory variables (X).

Table 1: Income categories of household.

Binary and Interval regression models were also used to double check for important determinants of households’ welfare determinants (for more details see Green, 2010). Both models were estimated using maxi category. The coefficient value mum likelihood estimation method.

Results and Discussion

Estimated ordered logistic model results

In the ordered logistic regression analysis, households monthly income order (1,2,3,4) was used as dependent variable and income generating individuals (IGI), milking animals (MA), women involvement in livestock production (WI), education level of the head (HEDU), age of the head (HAGE), and agricultural land (AL) of the household were used as independent explanatory variables. Results from maximum likelihood estimation are given in Table 2. Details on the estimated coefficients and their significance are discussed below.

Table 2: Estimated determinants of welfare through ordered logistic model.

Prediction with cut values: To find out the income (welfare) category of a household the data on the explanatory variables are placed in the estimated model and the outcome was compressed with cut values given at the bottom of the Table 2.

Cut1: is the estimated cut point on the latent variable used to differentiate the first income category from the other three categories. A value of 1.54 or less on the underlying latent variable that gave rise to income variable would be classified first income category.

Cut2: is the estimated cut point on the latent variable used to differentiate second category of income from 1st, 3rd and 4th categories when values of the predictor variables are evaluated at zero.

Cut3: This is the estimated cut point on the latent variable used to differentiate third category of income from 1st, 2rd and 4th categories.

Estimated probabilities

Table 3 shows the predicted probability for livestock farm household for each category of income. Results show that the most likely income categories are 2nd and 1st with probabilities of 0.38 and 0.24. These estimated results were consistent with percentages of households in different income categories given in Table 1.

Table 3: Predicted probabilities of ordered logit model.

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