Balanced technical progress

Although the main focus of the experimental work in this chapter is on asymmetric

technical progress - that is, a change occurring in only one of the two agricultural sectors - an intuitive grasp of the results is made easier by first considering the case in which a uniform, factor-neutral technical change occurs in sectors 1 and 2 together. Percentage changes in endogenous variables resulting from a uniform ten per cent change in the

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productivity of all factors in agriculture are reported in Tables 6-8 and 6-9. In these tables the total change in each variable is disaggregated into a component derived from the spending effect and a component derived from the resource movement effect. The latter is further divided between changes due to factor market adjustments and those caused by the real appreciation (the rise in P3). The subdivision of each total change in this model exposes the relative importance of factor market and consumption linkages, and of the agriculture-non-agriculture terms of trade, in determining the distributional outcomes of technical change shocks. In a more complete model (i.e. one with many more sectors), results disaggregated in this way would provide valuable guidance in policy formation for two reasons. Firstly, they would permit the identification of important cross-sector

linkages. Secondly, by laying bare the major adjustment mechanisms disaggregated results would reduce substantially the "black box" nature of CGE experiments, thus helping non-technical users of such models to gain an intuitive understanding of the results obtained.

The first column in Table 6-8 (headed ‘factor markets’) shows the effect of resource movements net of the appreciation in the real exchange rate. It is calculated by setting the expenditure elasticity of demand for the non-traded good ri3 to zero and holding constant the price of the non-traded service sector output. It therefore measures the effect of the boom in agriculture as transmitted through adjustments in factor markets only. In the agricultural sectors, output and factor demands rise as the result of technical progress. As was shown in Chapter 4, the effect of a neutral technical change on output supply is closely related to the effect of a rise in output price. Moreover, the empirical study of chapter 5 showed that producers in sector 1 (the stylised ‘well-irrigated’ area) are more price-responsive than their counterparts in sector 2, the ‘poorly irrigated’ area.

Accordingly, their output and associated factor demands rise by somewhat more. At constant output prices, the additional factor demand in agriculture is met by drawing capital and labour out of services and manufacturing. Numeraire prices of the mobile factors rise accordingly, with the greater increase accruing to labour, since that is the mobile factor used relatively intensively in agriculture.

Returns to fixed factors in the booming agricultural sectors rise by more than the amount of the technical change (as predicted for lower-dimensional models in Jones 1971), while returns to fixed factors in other sectors fall as increases in mobile factor prices reduce profitability. Numeraire GDP - defined as the sum of price and quantity changes for each commodity produced - rises by one-fifth of the rate of the technical change shock, i.e. by two per cent.

Table 6-8: Production and price effects of neutral technical progress shocks in both agricultural sectors

CT/ = T { = 10.00)

R e s o u r c e M o v e m e n t E f f e c t

Endogenous Factor Real Total RM Spending Total

Variable Markets Apprec’n Effect Effect Change

(1) (2) (3)=(l)+(2) (4) (5)=(3)+(4) Labour demand Agriculture 1 3.53 -0.31 3.23 -2.00 1.23 Agriculture 2 0.76 -0.08 0.68 -0.55 0.14 Services -1.32 0.54 -0.79 3.49 2.70 M ’facturing -1.88 -0.39 -2.27 -2.92 -5.19 Capital demand Agriculture 1 4.55 -0.35 4.12 -2.30 1.90 Agriculture 2 0.58 -0.03 0.55 -0.21 0.34 Services -0.69 1.14 0.45 7.32 7.78 M ’facturing -0.49 -0.72 -1.21 -4.71 -5.92 Product supply Agriculture 1 14.86 -0.29 14.56 -1.92 12.64 Agriculture 2 11.60 -0.08 11.52 -0.49 11.03 Services -1.47 1.11 -0.36 7.24 6.88 M ’facturing -1.47 -0.69 -2.16 -4.51 -6.68 Numeraire prices Labour 1.86 0.71 2.57 4.60 7.17 Capital 1.08 0.68 1.76 4.43 6.19 Services 0.00 1.80 1.80 11.75 13.56 F. factor 1 22.69 -1.04 21.65 -6.79 14.86 F. factor 1 18.29 -0.70 17.59 -4.56 13.03 F. factor 3 -3.57 4.39 0.83 28.62 29.45 F. factor 4 -3.30 -1.61 -4.92 -10.50 -15.41 GDP 2.11 0.79 2.90 5.11 8.01 Real Prices Labour 1.86 -0.05 1.81 -0.34 1.47 Capital 1.08 -0.08 1.00 -0.51 0.49 Services 0.00 1.05 1.05 6.82 7.86 F. factor 1 22.69 -1.80 20.89 -11.73 9.17 F. factor 2 18.29 -1.46 16.84 -9.50 7.34 F. factor 3 -3.57 3.63 0.07 23.68 23.75 F. factor 4 -3.30 -2.37 -5.67 -15.43 -21.11 Real GDP 2.11 0.03 2.14 0.17 2.32

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Table 6-9: Household income effects of neutral technical progress shocks in both agricultural sectors

(7y = 7 / = lo.oo)

Numeraire household incomes

Labourers 1.86 0.71 2.57 4.60 7.17 Urban 3 -2.17 3.28 1.11 21.36 22.47 Urban 4 -1.99 -0.92 -2.91 -6.02 -8.93 Landlords 1 11.89 -0.18 11.71 -1.18 10.52 Landlords 2 11.41 -0.15 11.26 -0.97 10.29 Farmers 1 7.80 0.17 7.97 1.11 9.08 Farmers 2 8.28 0.14 8.42 0.90 9.32

Household price indices

Labourers 0.00 0.36 0.36 2.35 2.71 Urban 3 0.00 1.08 1.08 7.05 8.13 Urban 4 0.00 1.08 1.08 7.05 8.13 Landlords 1 0.00 0.91 0.91 5.87 6.78 Landlords 2 0.00 0.72 0.72 4.70 5.42 Farmers 1 0.00 0.54 0.54 3.53 4.07 Farmers 2, 0.00 0.36 0.36 2.35 2.71

Real household incomes

Labourers 1.86 0.35 2.21 2.25 4.46 Urban 3 -2.17 2.20 0.03 14.31 14.33 Urban 4 -1.99 -2.01 -3.99 -13.07 -17.07 Landlords 1 11.89 -1.08 10.80 -7.06 3.75 Landlords 2 11.41 -0.87 10.54 -5.67 4.87 Farmers 1 7.80 -0.37 7.43 -2.41 5.02 Farmers 2 8.28 -0.22 8.06 -1.45 6.60

Totals may not be exact due to rounding errors.

Factor price changes are reflected in the incomes of the various household groups. Column 1 of Table 6-9 shows that the effects of factor market adjustments in isolation are to raise incomes of owners of the factors used more intensively in agriculture - labour and land. The greatest increases are won by landlords, with lesser increases to farmers (who own some land, some labour and some capital), and considerably lower gains accruing to labourers. Since commodity prices are held constant, numeraire and real income changes are the same for each group.

rise in the price of the non-traded good) which occurs because output in the services sector has fallen while demand has remained constant (recall that the resource movement effect is isolated by setting the income elasticity of demand r\3 to zero). Column 2 of each table shows the effect of the real appreciation net of the effects of changes in factor

prices, while column 3 of each table shows the total resource movement effect, inclusive of both factor and product price changes. At 1.8%, the extent of the real appreciation

(Pf) is substantial. As expected, the real appreciation raises profitability in the services sector, drawing mobile factors away from other sectors - and thereby bidding up their prices by a further 0.71% (labour) and 0.68% (capital). As a result, the output of the services sector recovers about half of the ground lost due to the initial boom in

agriculture: having fallen by 1.47%, the rise in P3 reduces the decline in output to -0.36%. Returns to the specific factor in sector 3, which were cut by 3.56% by the factor market adjustments, rise due to the real appreciation by 4.39%: the net impact of the resource movement effect on returns to this factor is positive, although small, at 0.83%. The largest falls in factor demand and output are found in the manufacturing sector. "De­ industrialisation" takes place both directly - through the movement of factors into agriculture - and indirectly through the real appreciation. The reallocation of resources due to the real appreciation raises GDP by another 0.79% - about one-third of its initial rise.

Real factor and commodity price changes are defined as nominal changes deflated by the GDP-share-weighted change in the price of services. In real terms the rise in services’ price due to the resource movement effect lowers wages and returns to mobile capital very slightly, and raises the return to the factor specific to the services sector. As the zero pure profit conditions require, the real change in P3 is "trapped between" - i.e. is a weighted average of - changes in the prices of factors used in the production of services.

Real changes in household income are obtained by deflating numeraire incomes by household-specific commodity price indices. On its own, the real appreciation

component of the resource movement effect redistributes some of the incremental income from the initial boom away from agriculturalists towards the owners of the factor specific to services: the real incomes of households in the group ‘Urban 3’ (who own all of sector 3’s specific factor) rise by 2.2%. Labourers also gain, but the rise in returns to their endowments of mobile capital is insufficient to offset the losses experienced by landlords and the owners of the specific factor in manufacturing.

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normal good, some of the additional income is spent in sector 3. Columns 4 and 5 in Tables 6-8 and 6-9 display - respectively - the changes in quantities, prices and incomes due to the spending effect of the boom, and the total changes in those variables due to both resource movement and spending effects. Since the numeraire prices of traded goods do not change, the spending effect measures the consequences of increased demand for services as transmitted through changes in the price of services, and thence to changes in wages and in the returns to mobile capital. For mobile and agriculture-specific factors, the magnitude of the real spending effect is much smaller than that of the resource movement effect; the reverse is true for the prices of non-agricultural factors.

The spending effect strengthens the recovery of output and factor demand in the services sector primarily at the expense of the manufacturing sector. Increased demand for services raises the numeraire price of services P3 by 11.75% - considerably faster than the rises in returns to mobile factors, and about six times faster than the equivalent rise associated with the resource movement effect. This contributes to a final outcome for

real factor returns (factor returns less the change in the price of the non-traded good, weighted by its share in GDP) which confirms a rise in wages (1.47%) about treble that in returns to mobile capital (0.49%). A large rise in the return to the factor specific to

services from the spending effect (23.68%) yields an overall rise in that factor’s real price of 23.75%. Real returns to manufacturing’s specific factor fall by 21.11%. Falls in returns to agriculture’s specific factors from the spending effect are much lower at -11.72% (sector 1) and -9.5% (sector 2). Finally, the spending effect has a small positive effect on real GDP, raising it by a further 0.17% above the change due to the resource movement effect alone; the total rise in real GDP is 2.32%. In Bautista’s (1986a) CGE model of the Philippines, a ten per cent increase in total agricultural productivity raised real GDP by the comparable figure of 2.17%.

In addition to the negative impact of the spending effect on real wages (and therefore on the incomes of labourers and small farmers), the larger share of services in the total expenditure of wealthy urban and (to a lesser extent) landlord households (Table 6-7, column 2) means that the real appreciation has a small equalising effect on the real incomes of household groups. The price indices of the Urban 3 and Urban 4 groups, as well as those of landlords, rise by about twice as much as do those of farmers and labourers. In addition, the spending effect brings no additional income to owners of specific factors except in the non-traded goods sector. As a result labourers - whose income gain from the resource movement effect was only one quarter to one fifth that of owners of agriculture-specific factors - finally enjoy an income rise larger than that of

landlords, and nearly as great as that of farmers. In their analysis of the redistributive effects of a boom, Corden and Neary (1985) noted that the likelihood that growth in the booming sector could actually reduce returns to that sector’s specific factors is greater, the larger is the spending effect relative to the resource movement effect. The results of this analysis appear to confirm their addendum that such an outcome requires "a rather implausible set of parameter values" (p.233). In this experiment, even what appears to be a strong spending effect is dominated by the resource movement effect’s impact on fixed factor returns, making the possibility of a fall in the returns to landowners remote. This conclusion can be drawn with some confidence given the robustness of the model to changes in parameter values (see section 6.4.5).