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Dynamic and Static Behaviour with Respect to Energy Use and Investment of Dutch Greenhouse Firms

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Abstract

Dutch greenhouse horticulture firms are energy-intensive and major emitters of greenhouse gases. This paper develops a theoretically consistent model that is able to describe the greenhouse firms’ behaviour regarding energy use and investments in energy technology. The behaviour of the firm is modelled using a combination of a dynamic cost function and a static profit function framework. The optimal quantity of energy is derived from the link between these two functions. The model is applied to a panel of 97 Dutch greenhouse firms over the period 2001–2008. The results show that most Dutch greenhouse firms shift from being net electricity users to net electricity producers in the long term. Investing in energy capital contributes to reducing net energy use, however it increases the quantity of carbon dioxide emissions due to an increase in electricity production. A 1 % increase of the price of gas reduces carbon dioxide emissions by 1.6 %.

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Notes

  1. The two simultaneous differential equations cannot easily be solved analytically; however, an approximation to the solution is taken to solve the problem. In our case, investment demand in the long-term (\(\dot{K}^{*})\) is approximated by \(\frac{dK^{*}}{dt}\).

  2. Our panel data set includes 54.54 % observations with a positive investment, 44.79 % of observations with no (zero) investment and 0.67 % observations with a negative investment.

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Acknowledgments

We gratefully acknowledge the Agricultural Economics Research Institute (LEI) for making the data available for this study and we would like to thank the anonymous referees for their valuable comments.

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Correspondence to D. M. I. Verreth.

Appendices

Appendix A

1.1 Estimation results

Parameter

Estimate

SE

Parameter

Estimate

SE

\(a_{11}\)

268.877

91.05**

\(g_{4}\)

5.561

7.232

\(a_{12}\)

\(-\)25.891

101.6

\(g_{5}\)

0.01129

0.018

\(a_{22}\)

96.732

308.6

\(g_{6}\)

\(-\)880.968

1958.2

\(\beta _{1}\)

\(-\)211.088

46.44**

\(g_{11}\)

\(-\)1866.29

2448.4

\(\beta _{2}\)

117.744

37.65**

\(g_{12}\)

2891.196

2405.3

\(\beta _{3}\)

0.276

0.079**

\(g_{13}\)

\(-\)14464.2

20014.1

\(\beta _{4}\)

0.763

0.12**

\(g_{22}\)

\(-\)4633.74

2465.9*

\(\beta _{11}\)

16.465

13.299

\(g_{23}\)

17777.23

10471.9*

\(\beta _{22}\)

\(-\)25.789

6.55**

\(g_{33}\)

\(-\)136522

429762

\(\beta _{33}\)

\(-\)0.00006

0.00003*

\(Q_{11}\)

0.003126

0.00409

\(\beta _{44}\)

0.00007

0.000019**

\(Q_{12}\)

\(-\)0.00006

0.000039

\(\beta _{55}\)

\(-\)7.238

4.72

\(Q_{13}\)

0.1694

0.2684

\(\beta _{12}\)

13.829

6.45**

\(Q_{22}\)

\(4.129^{-6}\)

\(6.472^{-6}\)

\(\beta _{13}\)

0.0000158

0.018

\(Q_{23}\)

0.000713

0.00383

\(\beta _{14}\)

0.004219

0.01

\(Q_{33}\)

\(-\)30.7669

69.527

\(\beta _{15}\)

\(-\)19.625

6.06**

\(R_{11}\)

21.7229

2.3388**

\(\beta _{23}\)

\(-\)0.0299

0.013**

\(R_{12}\)

7.408

2.1766**

\(\beta _{24}\)

0.0078

0.0036**

\(R_{13}\)

\(-\)4.0637

7.516

\(\beta _{25}\)

2.438

2.98

\(R_{21}\)

\(-\)0.09834

0.0319**

\(\beta _{34}\)

\(2.01^{-6}\)

\(-9.68^{-6}\)

\(R_{22}\)

0.11279

0.0349**

\(\beta _{35}\)

\(-\)0.00398

0.01

\(R_{31}\)

\(-\)52.947

248.9

\(\beta _{45}\)

0.0117

0.010

\(R_{32}\)

\(-\)115.443

270.3

\(\gamma _{11}\)

296.03

25.95**

\(D_{1}\)

\(-\)195.057

63.307**

\(\gamma _{12}\)

\(-\)69.609

20.272**

\(D_{2}\)

238.703

64.27**

\(\gamma _{13}\)

\(-\)0.0289

0.043

\(R_{33}\)

\(-\)2.33484

55.17

\(\gamma _{14}\)

0.226

0.087**

\(R_{23}\)

\(-\)0.288817

0.0603**

\(\gamma _{21}\)

60.9398

23.26**

\(\sigma \)

269.77

128.3**

\(\gamma _{22}\)

139.87

17.955**

   

\(\gamma _{23}\)

\(-\)0.023

0.038

   

\(\gamma _{24}\)

0.269

0.1408*

   
  1. Asterisk (*) and double asterisk (**) denote significance at 10 and 5 %, respectively

Appendix B

1.1 Elasticities for CO\(_{2}\)

Using both the direct and the indirect effects, one can derive the responses of CO\(_{2}\) emissions quantity to a change in an energy input price. In the short term, the CO\(_{2}\) emission elasticities show the effect of a price change before adjustments in energy capital or energy quantity have taken place. The short-term CO\(_{2}\) emission elasticity is:

$$\begin{aligned} \varepsilon _{E^{*}gas}^{SR} =\left[ {\frac{dGas}{dw_m }+\frac{dGas}{dE^{*SR}}\frac{dE^{*SR}}{dw_m }} \right] \frac{w_m }{Gas}. \end{aligned}$$

The first term between the brackets corresponds to the direct effect to a change in price \(w_{m}\), and indicates the response of the quantity of gas to the change in price. The second term between the brackets is the indirect effect that corresponds to the response of gas quantity to a change in the price when the quasi-fixed input energy quantity is optimal in the short term.

In the long term, energy output and the quasi-fixed input energy capital could adjust to their optimal levels. Now the responses of the specific quantity to a gas price change when energy capital and the output energy quantity fully have adjusted to their long-term equilibrium level, are taken into account. In the long term, the responses of gas quantity to a change in optimal energy quantity or optimal energy capital are derived from Eqs. (25a) and (26). The long term CO\(_{2}\) emission elasticity is expressed as:

$$\begin{aligned} \varepsilon _{E^{*}gas}^{LR} =\left[ {\frac{dGas}{dw_m }+\frac{dGas}{dE^{*LR}}\frac{dE^{*LR}}{dw_m }+\frac{dGas}{dK^{*}}\frac{dK^{*}}{dw_m }} \right] \frac{w_m }{Gas}. \end{aligned}$$

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Verreth, D.M.I., Emvalomatis, G., Bunte, F. et al. Dynamic and Static Behaviour with Respect to Energy Use and Investment of Dutch Greenhouse Firms. Environ Resource Econ 61, 595–614 (2015). https://doi.org/10.1007/s10640-014-9808-6

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