We apply a range of analytical tools to address the four key research objectives. These include: (a) computation of annual compound growth rates of key indicators of performance; (b) construction of a policy analysis matrix (PAM) and computation of selected ratio indicators to measure the global competitiveness of the sector; (c) a cost-benefit analysis (CBA) to determine the financial profitability of jute production at the farm level; and (d) a stochastic production frontier (SFA) approach to estimate the productivity and technical efficiency of jute production and its drivers at the farm level. The details are as follows.
2.1. Trend Analysis of the Jute Sector Average annual compound growth rates were computed in order to determine the rate of change of the variable of interest (i.e., cultivated area, total production, yield, harvest price, and value of jute exported). The growth rates were computed using a semi-logarithmic trend function: lnY = α + βT, where Y is the target variable, T is time, ln is the natural logarithm, and β is the growth rate.
2.2. Analysis of Competitiveness of Jute A PAM framework was utilized to analyze the competitiveness and economic efficiency of jute production. The PAM framework is particularly useful in identifying the appropriate direction of change in policy and is commonly used for policy analysis. The process uses two enterprise budgets, one valued at market prices and the other valued at social prices. Profit in the PAM framework is defined as the difference between the total (or per unit) revenues minus total production costs. Each PAM consists of two cost columns, one for the tradable inputs and the other for domestically produced factors. The matrix presents an array of symbols or letters which define accounting relationships across the columns of the matrix and down the rows of the matrix. Such relationships are termed as identities.
The indicators in the first row provide a measure of private profitability (D), or competitiveness, and is defined as the difference between observed revenue (A) and costs (B + C). Private profitability demonstrates the competitiveness of the system, given current technologies, prices of inputs and outputs, and policy interventions and market failures. The second row of the matrix calculates the measure of social profitability (H) defined as the difference between social revenue (E) and costs (F + G). Social profitability measures economic efficiency/comparative advantage of the system. To estimate social prices, the inputs used were divided into two categories: (a) tradable intermediate inputs; and (b) non-tradable intermediate inputs. The tradable intermediate inputs were different types of fertilizers and irrigation equipment. We have used an import parity price by converting the FOB price to CIF at the Chittagong port by adding the freight cost to FOB prices of fertilizers (for details, please see Molla et al. [20]). Since, detailed cost of production for irrigation equipment are not available, it was not considered. For the non-tradable intermediate inputs, such as agricultural labor, machinery, seed, organic manure, insecticides, cultivated land, irrigation fees, and interest on operating capital, we have applied domestic costs adjusted with specific conversion factors (SCF) for each input (for details of full social costs and SCF, see Kazal et al.; Shahabuddin and Dorosh, The opportunity cost of operating capital was calculated at an interest rate of 10% for the duration of the jute production period.
2.3. Ratio Indicators of Competitiveness The PAM framework can also be used to calculate important indicators for policy analysis. Popular measures of global competitiveness are: the nominal protection coefficient (NPC) and effective protection coefficient (EPC). We apply the NPC on output (NPCO) and input (NPCI), as well as the EPC to determine the competitiveness of jute.