Derivations

This appendix contains derivations from the theory in the body of this book.

Properties of the CES Production Function

The constant elasticity of substitution (CES) production function of capital and labor was introduced by [Solow, 1956] and further extended to a consumption aggregator by [Armington, 1969]. The CES production function of aggregate capital \(K_t\) and aggregate labor \(L_t\) we use in Chapter Firms is the following,

(123)\[ Y_t = F(K_t, K_{g,t}, L_t) \equiv Z_t\biggl[(\gamma)^\frac{1}{\varepsilon}(K_t)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g,t})^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(e^{g_y t}L_t)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \quad\forall t\]

where \(Y_t\) is aggregate output (GDP), \(Z_t\) is total factor productivity, \(\gamma\) is a share parameter that represents private capital’s share of income in the Cobb-Douglas case (\(\varepsilon=1\)), \(\gamma_{g}\) is public capita’s share of income, and \(\varepsilon\) is the elasticity of substitution between capital and labor. The stationary version of this production function is given in Chapter Stationarization. We drop the \(t\) subscripts, the ``\(\:\,\hat{}\,\:\)’’ stationary notation, and use the stationarized version of the production function (82) for simplicity.

(124)\[ Y= Z\biggl[(\gamma)^\frac{1}{\varepsilon}(K)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g})^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(L)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \quad\forall t\]

The Cobb-Douglas production function is a nested case of the general CES production function with unit elasticity \(\varepsilon=1\).

(125)\[ Y = Z(K)^\gamma(K_{g})^{\gamma_{g}}(L)^{1-\gamma-\gamma_{g}}\]

Wages as a function of interest rates

The below shows that with the addition of public capital as a third factor of production, wages and interest rates are more than a function of the capital labor ratio. This means that in the solution method for OG-Core we will need to guess both the interest rate \(r_t\) and wage \(w_t\).

(126)\[\begin{split}\begin{split} Y &= Z\biggl[(\gamma)^\frac{1}{\varepsilon}(K)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g})^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(L)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \\ &= Z\biggl[(\gamma)^\frac{1}{\varepsilon}(K)^\frac{\varepsilon-1}{\varepsilon}\left(\frac{L^\frac{\varepsilon-1}{\varepsilon}}{L^\frac{\varepsilon-1}{\varepsilon}}\right) + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g})^\frac{\varepsilon-1}{\varepsilon}\left(\frac{L^\frac{\varepsilon-1}{\varepsilon}}{L^\frac{\varepsilon-1}{\varepsilon}}\right) + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(L)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \\ &= ZL\biggl[(\gamma)^\frac{1}{\varepsilon}\left(\frac{K}{L}\right)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{K_{g}}{L}\right)^\frac{\varepsilon-1}{\varepsilon}+ (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1}\\ \Rightarrow\quad \frac{Y}{L} &= Z\biggl[(\gamma)^\frac{1}{\varepsilon}\left(\frac{K}{L}\right)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{K_{g}}{L}\right)^\frac{\varepsilon-1}{\varepsilon}+ (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \end{split}\end{split}\]
(127)\[\begin{split}\begin{split} Y &= Z\biggl[(\gamma)^\frac{1}{\varepsilon}(K)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g})^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(L)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \\ &= Z\biggl[(\gamma)^\frac{1}{\varepsilon}(K)^\frac{\varepsilon-1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}(K_{g})^\frac{\varepsilon-1}{\varepsilon}\left(\frac{K^\frac{\varepsilon-1}{\varepsilon}}{K^\frac{\varepsilon-1}{\varepsilon}}\right) + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}(L)^\frac{\varepsilon-1}{\varepsilon}\left(\frac{K^\frac{\varepsilon-1}{\varepsilon}}{K^\frac{\varepsilon-1}{\varepsilon}}\right)\biggr]^\frac{\varepsilon}{\varepsilon-1}\\ &= ZK\biggl[(\gamma)^\frac{1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{K_{g}}{K}\right)^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{L}{K}\right)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \\ \Rightarrow\quad \frac{Y}{K} &= Z\biggl[(\gamma)^\frac{1}{\varepsilon} + (\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{K_{g}}{K}\right)^\frac{\varepsilon-1}{\varepsilon} + (1-\gamma-\gamma_{g})^\frac{1}{\varepsilon}\left(\frac{L}{K}\right)^\frac{\varepsilon-1}{\varepsilon}\biggr]^\frac{\varepsilon}{\varepsilon-1} \end{split}\end{split}\]

Solving for the firm’s first order conditions for capital and labor demand from profit maximization (83) gives the following equations in their respective stationarized forms from Chapter Stationarization.

(128)\[ w = (Z_t)^\frac{\varepsilon-1}{\varepsilon}\left[(1-\gamma-\gamma_{g})\frac{Y}{L}\right]^\frac{1}{\varepsilon}\]
(129)\[ r = (1 - \tau^{corp})(Z)^\frac{\varepsilon-1}{\varepsilon}\left[\gamma\frac{Y}{K}\right]^\frac{1}{\varepsilon} - \delta + \tau^{corp}\delta^\tau\]

As can be seen from (128) and (129), the wage \(w\) and interest rate \(r\) are functions of \(Y/L\) and \(Y/K\), respectively. Equations (126) and (127) show that both \(Y/L\) and \(Y/K\) are functions of the capital-labor ratio \(K/L\), the public-capital-labor ratio, \(K_{g}/L\), and the public-private capital ratio, \(K/K_{g}\). We cannot solve these equations for \(r\) and \(w\) solely as functions of the same ratios.

In the Cobb-Douglas unit elasticity case (\(\varepsilon=1\)) of the CES production function, the first order conditions are:

(130)\[ \text{if}\:\:\,\varepsilon=1:\quad w = (1-\gamma-\gamma_g)Z\left(\frac{K}{L}\right)^\gamma \left(\frac{K_{g}}{L}\right)^{\gamma_{g}}\]
(131)\[ \text{if}\:\:\:\varepsilon=1:\quad r = (1 - \tau^{corp})\gamma Z\left(\frac{K_{g}}{K}\right)^{\gamma_{g}}\left(\frac{L}{K}\right)^{1-\gamma-\gamma_{g}} - \delta + \tau^{corp}\delta^\tau\]

Again, even if this simple case, we cannot solve for \(r\) as a function of \(w\) for the reasons above.