snqProfitCalc            package:micEcon            R Documentation

_C_a_l_c_u_l_a_t_i_o_n_s _w_i_t_h _t_h_e _S_N_Q _P_r_o_f_i_t _f_u_n_c_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Calculation of netput quantities and profit with the Symmetric
     Normalized Quadratic (SNQ) Profit function.

_U_s_a_g_e:

        snqProfitCalc( pNames, fNames, data, weights, coef, form = 0  )

_A_r_g_u_m_e_n_t_s:

  pNames: a vector of strings containing the names of netput prices.

  fNames: an optional vector of strings containing the names of the
          quantities of (quasi-)fix inputs.

    data: a data frame containing the data.

 weights: vector of weights of the prices for normalization.

    coef: a list containing the coefficients alpha, beta, delta and
          gamma.

    form: the functional form to be estimated (see 'snqProfitEst').

_V_a_l_u_e:

     a data frame: the first n columns are the netput quantities, the
     last column is the profit.

_A_u_t_h_o_r(_s):

     Arne Henningsen ahenningsen@agric-econ.uni-kiel.de

_R_e_f_e_r_e_n_c_e_s:

     Diewert, W.E. and T.J. Wales (1987) Flexible functional forms and
     global curvature conditions. _Econometrica_, 55, p. 43-68.

     Diewert, W.E. and T.J. Wales (1992) Quadratic Spline Models for
     Producer's Supply and Demand Functions. _International Economic
     Review_, 33, p. 705-722.

     Kohli, U.R. (1993) A symmetric normalized quadratic GNP function
     and the US demand for imports and supply of exports.
     _International Economic Review_, 34, p. 243-255.

_S_e_e _A_l_s_o:

     'snqProfitEst' and 'snqProfitWeights'.

_E_x_a_m_p_l_e_s:

        data( germanFarms )
        germanFarms$qOutput   <- germanFarms$vOutput / germanFarms$pOutput
        germanFarms$qVarInput <- -germanFarms$vVarInput / germanFarms$pVarInput
        germanFarms$qLabor    <- -germanFarms$qLabor
        germanFarms$time      <- c( 0:19 )
        pNames <- c( "pOutput", "pVarInput", "pLabor" )
        qNames <- c( "qOutput", "qVarInput", "qLabor" )
        fNames <- c( "land", "time" )

        estResult <- snqProfitEst( pNames, qNames, fNames, data = germanFarms )
        snqProfitCalc( pNames, fNames, estResult$estData, estResult$weights,
           estResult$coef )

