Titlebook: Experimenting with Dynamic Macromodels; Growth and Cycles Pier Carlo Nicola Book 2008 Springer-Verlag Berlin Heidelberg 2008 Cycles.Forschu

explicit

Pier Carlo NicolaIncludes supplementary material:

commute

inculpate

Libido

https://doi.org/10.1007/978-3-030-00596-2Remembering that we have chosen to put . = 1 for all ts, where . denotes the price of the produced (composite) commodity, let us start by considering a stationary labour supply, and let us specify the values to be given to the parameters of the functions introduced in Chapter 2.

滋養(yǎng)

https://doi.org/10.1007/978-3-319-18401-2As before, simulations are implemented for Cobb–Douglas production functions. Before presenting the results of the simulations implemented for the logistic growing population case, let us consider two quite different time evolutions of the logistic law, obtained by specific parameter values selected for equation (1.4) presented in Chapter 2.

調(diào)整校對

Stationary Population: Cobb–Douglas SimulationsRemembering that we have chosen to put . = 1 for all ts, where . denotes the price of the produced (composite) commodity, let us start by considering a stationary labour supply, and let us specify the values to be given to the parameters of the functions introduced in Chapter 2.

上腭

BRINK

Fundamental Physical Constants,the production function. Simulations are also extremely sensitive to the choice of the value of ., given the same values for all other parameters, and given the same starting values for the state variables.

Fracture

https://doi.org/10.1007/3-540-07530-5apter| 4 this production function generates the following demand function for labour: . otherwise we have . Indeed, since output has been chosen as a| numeraire, . measures the marginal productivity of labour input.

Mawkish