have more potential to impact on poverty than indirect pathways from large-scale commercial operations and direct and indirect pathways from small-scale pond aquaculture.
To test Hypothesis 2 and explore the linkages arising from different aquaculture systems, a number of data sources and methodologies are utilised as follows: i) the household survey of small-scale fish farmers in Ashanti Region described in Section 4.3.1 above: ii) an enterprise survey of SME and large-scale cage farms in Lake Volta in the two study districts in Eastern Region; and iii) FGDs conducted in seven communities on Lake Volta where cage aquaculture is present. The communities in which the surveyed cage farms are located are shown in Figure 10.
Economic multiplier effects are calculated using a semi input-output multiplier model using data from the small-scale fish farming PBs described in Section 4.3.1, budget data from the cage farm survey, and expenditure data from the GLSS5. Employment generated by different systems along with wage rates is calculated using data from the household survey and the cage farm enterprise survey. These data sources and methodologies are described in turn below (aside from the household survey and PBs). All survey data is analysed using SPSS Version 16.
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Figure 10: Location of cage farms surveyed in the two study districts
Cage farm enterprise survey and community FGDs
A cage farm enterprise survey was undertaken in early 2011 in the two study districts in Eastern Region. A sampling frame of 54 functional SME and large-scale cage farms was constructed with the help of the District FC and Water Research Institute (WRI) staff in Akosombo. A large number of cage farms on record at the District FC Office were no longer functional. As many as possible of the functional cage farms were visited. In total 14 small-scale, 5 medium-scale and 2 large-scale commercial cage farms were surveyed (shown in Figure 10) and owners and/or caretakers were interviewed. The survey collected information for 2010 on: i) farmers’ socioeconomic characteristics; ii) production systems and practices including number and size of cages and levels of inputs; iii) fish production and revenue; iv) farm
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employment and wages; v) marketing channels; vi) costs and revenues; and vii) linkages with and impacts on surrounding communities. The full questionnaire is presented in Appendix 2.
FGDs were conducted with 7 communities on Lake Volta where cage aquaculture is present. The communities were chosen to represent the range of small, medium and large-scale farms (and one community, where a private hatchery, previously a commercial cage farm, is located was also chosen) to understand the linkages arising from different systems. The FGDs were undertaken with groups of 8-12 community members of mixed ages and genders, and gathered information on: i) community characteristics and distribution of poverty; ii) main livelihood activities of community members, iii) employment linkages from cage farms (including data on groups benefiting from seasonal and regular employment, trading and processing due to cage aquaculture); iii) cost of living linkages, and price and food security impacts on consumption of fish by poor households; iv) consumption linkages; and v) institutional, service and infrastructure linkages from cage farms. Short FGDs were also conducted with fishermen in these 7 communities to understand the positive and negative impacts of cage aquaculture on fishermen’s livelihoods (if any) such as changes in access rights to fishing grounds.
Multiplier estimation
A fixed-price semi input-output multiplier model is used to estimate the economic multiplier effects arising from development of small-scale pond aquaculture in Ashanti Region and commercial SME cage aquaculture in Lake Volta, Eastern Region. The model used here, like most economic multiplier models in the literature, only considers the effects of backward and forward production linkages and consumption linkages on economic growth.
Investment, cost of living, environmental, service and institutional linkages (described in Chapter 2) are excluded from the calculations. However results from Chapter 6 indicate that production and consumption linkages are the strongest of all the possible linkages from aquaculture.
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Many of the models used in linkage studies are variants of the original semi input-output model developed by Bell and Hazell (1980), for example Bell, Hazell and Slade (1982), Haggblade and Hazell (1989) which used a three sector variant and Delgado et al. (1998) which used a four sector variant. The model describes an economy in which gross output consists of tradable output T, assumed to be fixed at T, as tradable goods are assumed to be supply constrained, plus nontradable outputs, N, the supply of which is assumed to be highly elastic.
As discussed in Chapter 2, Section 2.3.4, nontradable goods are those that are produced and consumed locally, having either no outside markets or external sources of demand. Furthermore, nontradable goods must not have close tradable substitutes that are available locally, so the domestic price of the non traded good is not likely to be highly correlated with the domestic price of any tradable good that could play the same role in the consumption basket (Delgado et al., 1998:1). Nontradables are demand constrained so any increased demand through income growth must be met by new production leading to additional growth in the local economy. This thesis uses both the regional and the national definition of trading space to calculate regional (local) and national multiplier effects. Thus the classification of a commodity as tradable or nontradable depends on whether the commodity is imported or exported from the trading space (in this case Ashanti Region/Eastern Region or Ghana) or has any locally available substitutes whose prices are correlated with it. While farmed fish produced by small-scale pond farmers in Ashanti Region are generally not traded outside the region let alone the country, and while tilapia from SME cage farms are traded outside Eastern Region but are not exported, aquaculture products are still treated here as tradables as they have locally available tradable substitutes (fish from marine and inland capture fisheries in Ghana and imported fish) whose prices are correlated.
The model measures the impact on a region’s income of an exogenous shock to a sector, via technological change or outside investment, enabling the region to increase its output of tradables and causing the output of
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nontradables to increase. Assuming the level of intermediate inputs used per unit of tradable output does not change due to the initial increase in tradable output (Haggblade et al., 1991), Bell and Hazell’s (1980) multiplier (M) can be written (Delgado et al., 1998:10):
where:
, = the share of nontradable intermediate inputs in nontradable and tradable output respectively (between 0 and 1),
, = the share of tradable intermediate inputs in nontradable and tradable output respectively (between 0 and 1),
= a constant with a value equal to 1 - - , the share of value added in gross output of the nontradables sector,
= same as but for tradables, with value equal to 1 - - = marginal propensity to consume nontradables (or MBS of
nontradables)
s = leakage, a constant proportion of total income (savings and tax rate)32.
The MBS for nontradables as a group is the most important determinant of the magnitude of estimated growth multipliers (Delgado et al., 1998). The actual multiplier is a numerical solution to a regional level model of supply and demand which incorporates household demands and intermediate demands between sectors (Delgado et al., 1998). This model is used to estimate the regional and national economic multiplier effects (i.e. the effect on regional and national income) of a one dollar increase in income from:
i) small-scale pond aquaculture in Ashanti Region and
ii) SME commercial cage aquaculture in Eastern Region, Ghana.
32 The multiplier and parameter definitions are taken directly from Delgado et al. (1998:10).
101 Parameter estimation and data
The model parameters are estimated using a mixture of primary and secondary data. The share of nontradable intermediate inputs in nontradable output ( )is estimated from the results of a previous study of agricultural multipliers in Ghana by Al-Hassan and Jatoe (2007). The share of nontradable intermediate inputs in tradable (i.e. aquaculture) output ( ) are estimated from primary budget data collected through PBs of small-scale pond farmers, and survey data of SME cage farmers supplemented by data from key informant interviews. The ratio of value added in gross output of the nontradables sector ( ) is also estimated from the results of Al-Hassan and Jatoe (2007), and the ratio of value added in gross output of the tradable aquaculture sector ( ) is estimated from the primary budget data described above. The savings rate (s) is estimated from Ghana National Accounts data for 2010.
The MBS of nontradables ( n) is calculated by empirically estimating expenditure functions for nontradable goods using expenditure data from the GLSS5. Goods were classified into nationally tradable and nontradable categories according to the definition given above. As there was only one pond farmer and no cage farmers captured by the GLSS5, the expenditure of cocoa farmers in Ashanti Region is used as a proxy for expenditure of small-scale pond farmers in Ashanti and the expenditure of professionals from Greater Accra who also had agricultural income is used as a proxy for SME cage farm owners. These proxies were chosen as the majority of small-scale pond farmers surveyed in Ashanti Region were also cocoa farmers and the majority of small-scale cage farm owners surveyed were professionals living in Accra.
An Engel curve relates the household budget shares allocated to each good to total household expenditure. A number of functional forms of the Engel curve have been developed in the economics literature (Deaton and Muellbauer, 1980). A popular form is the Working-Leser model (Working,
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1943, Leser, 1963) where the budget share of each good is a linear function of the logarithm of total household expenditure which can be expressed as:
(1)
where is the budget share of good j in household i (so if j is the group of nontradable goods, represents the ratio of expenditure on nontradable goods to total household expenditure), is total household expenditure, and are parameters to be estimated and is an error term. An expression to estimate the MBS of nontradable goods can be derived from this equation (shown in Appendix 3).
A variant of the Working-Leser model is used to estimate the MBS of nontradable goods in this thesis, using total expenditures as a proxy for income. MBS thus represents marginal propensities to consume. The basic Working-Leser model has been expanded to include other variables such as socio-economic and demographic household characteristics assumed to affect the budget shares allocated to different types of goods (see Deaton, 1997). Household characteristics are therefore included in the model used here which takes the following form:
, (2)
where is the budget share of category j of goods (in this case the share of nontradable goods) in household i, is total expenditure of household i, is a vector of household characteristics (household size, sex of household head and age of household head), and are parameters to be estimated, is an unknown parameter vector to be estimated and relates to household characteristics contained in the vector, and is an error term. The estimation technique used is the OLS procedure. The MBS values for nontradables were estimated with the assistance of an econometrician from the University of Ghana, Legon.
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Estimation of employment generation and wages
The level of employment generated by small-scale pond aquaculture is compared to the employment generated by crop farming and also by SME and large-scale commercial cage aquaculture using data collected from the household survey and from data collected from the cage farm enterprise survey. Employment is measured in full-time equivalent (FTE) jobs based on the number of days usually worked in the farming sector so one FTE job is estimated to represent one full time job for someone working 8 hours a day, 300 days a year. Wage rates between labourers on small-scale pond farms and SME cage farms are also estimated and compared to average wage rates in the agricultural sector.
Labourer characteristics
Some demographic characteristics of labourers on SME and large-scale commercial farms are explored using data collected from a survey of labourers. 86 employees on 3 small-scale farms, 5 medium-scale farms, 2 large-scale farms and the largest hatchery (Crystal Lake) were selected at random to be interviewed. The questionnaire is presented in Appendix 4.
4.3.3 Data and methods to test Hypothesis 3
This section reviews Objective 3 and Hypothesis 3, and then describes the main data sources, methods for data collection and analysis used to test Hypothesis 3.