The Energy Efficiency of Italian firms

1. The Energy Efficiency of Italian firms Ivan Faiella Ivan.Faiella@bancaditalia.it 34th IAEE International Conference, 22nd June 2011

2. The Energy Efficiency of Italian firms Outline of the presentation • Energy use in the industry sector • Energy efficiency (EE) as a policy option • EE analyses in the economic literature • Firm-level data on investments in EE: descriptive analysis and econometric estimates • Preliminary conclusions (positive and normative)

3. The Energy Efficiency of Italian firms Energy industrial use in Italy Final energy use of Industry by sub-sector (2007 - percentages of 39,7 Mtoe) Source: Our computations on ENEA data.

4. The Energy Efficiency of Italian firms Source: Our computations on MISE and Istat data. Energy industrial use in Italy Final energy use of Industry by fuel(Mtoe)

5. The Energy Efficiency of Italian firms Source: Odysee. Energy industrial use in Italy Energy intensity(Energy use per unit of real value added)

6. The Energy Efficiency of Italian firms Source: Our computations on Istat data. Energy industrial use in Italy Energy purchases

7. The Energy Efficiency of Italian firms Source: Our computations on Eurostat data. Industrial users, 1st semester 2009. Energy industrial use in Italy Energy prices: differential Italy vs EU27

8. The Energy Efficiency of Italian firms Source: IEA (2010), “Energy Technology Perspectives 2010”. EE: the best energy policy in the world… Potential savings from adopting BATs in industry(world)

9. The Energy Efficiency of Italian firms EE measures in the industrial sector Energy savings in 2016 (ktoe) Lighting systems 189 Motor systems 292 Inverters 550 CHP 540 Compressed air 280 Total 1,852 (4.8 per cent of industry energy use) Source: MISE. EE: the best energy policy in Italy … Potential savings from EE measures in industry(Italy)

10. The Energy Efficiency of Italian firms Source: Stoft (1995). Firms decision on EE “It is almost as widely accepted that much un-adopted technology is cost-effective at current prices“ (Jaffe and Stavins, 1994)

11. The Energy Efficiency of Italian firms Firms decision on EE The literature Theoretical framework to explain this “EE gap” • EE PARADOX: Jaffe and Stavins (1994) shows that this is due to market (lack of information, split-incentives, subsidies) and non-market (transaction costs, learning, discount rates) failures. • OPTION VALUE ASSOCIATED WITH POSTPONING EE INVESTMENTS: Dixit and Pindyck (1994) argument that investing in a more energy-efficient technology may turn out to be unprofitable if energy prices fall after the new technology has been implemented.

12. The Energy Efficiency of Italian firms The barriers to EE Source: Schleich (2007).

13. The Energy Efficiency of Italian firms Firms decision on EE Firm’s characteristics matter! • Empirical analyses of the determinant of EE investments The standard theory holds that the discount rate for computing the present value of a project should depend on projects traits (e.g. risk class) , and therefore should not depend on characteristics of the firm…but empirical results does not support the theory (DeCanio and Watkins, 1998). A wide range of company-specific characteristics is statistically associated with EE decisions; • The investments in EE is positively correlated with firm size and performance (DeCanio and Watkins, 1998), cost savings (de Groot et al., 2001), stringency of environmental regulation (Arvanitis and Ley, 2010) and managerial practices (Martin et al., 2010); • The investments in EE is negatively associated with payback time and investment costs (Martin et al., 2010 ; Abadie et al., 2011); but also to uncertainty (Kounetas and Tsekouras, 2008), and consumer prices (Ratti et al. 2011).

14. The Energy Efficiency of Italian firms Firm-level data on investments in EE • The investments in energy efficiency are examined using the Survey of Industrial and Service Firms (Invind) conducted yearly by the Bank of Italy (Bank of Italy, 2009). • Invind collects a wealth of information on a panel of about 4,000 Italian firms with more than 20 employees; in 2009 this information was integrated with a section on the investments to improve energy efficiency. • 2,821 firms of the industry+energy answers the questions: in the raw data about 11% disclosed the amount invested in EE. • The proportion of missing items is 16%. To avoid a bias in the estimates, missing items are imputed using a set of stochastic regression under the MAR hyp. (see Rubin, 1976; for an application to energy analysis, De Canio and Watkins, 1998).

15. The Energy Efficiency of Italian firms INV EE 2008 INV EE 2009 Sample Missing items (%) Missing items (%) Units Size (employees) 10.4 10.2 1,038 20 - 49 50 - 99 15.7 15.1 650 100 – 199 17.4 17.4 489 200 – 499 20.6 19.8 383 500 – 999 30.0 30.0 140 1.000 + 37.2 35.5 121 Sectors 17.1 16.1 322 Textiles, clothing, leather and footwear Chemicals, rubber and plastic 17.2 16.6 296 Basic metals and engineering 17.6 17.3 1,113 Other manufacturing (wood, pulp,oth.) 14.0 13.7 974 Energy and extraction 19.8 19.8 116 Total 16.3 16.0 2,821 Source: Our computations on Invind data. Firm-level data on investments in EE

16. The Energy Efficiency of Italian firms INV EE 2008 INV EE 2009 Diffusion (%) Average (k€) Diffusion (%) Average (k€) Size (employees) 23 20 24 18 20 - 49 50 - 99 30 30 32 30 100 – 199 36 35 38 30 200 – 499 42 70 43 63 500 – 999 52 101 55 99 1.000 + 68 376 67 397 distribution of the fixed costs Sectors 34 20 33 13 Textiles, clothing, leather and footwear Chemicals, rubber and plastic 26 28 28 37 Basic metals and engineering 26 27 26 20 Other manufacturing (wood, pulp,oth.) 25 36 27 34 Energy and extraction 27 23 31 92 Total 27 28 28 26 Source: Our computations on Invind data. Firm-level data on investments in EE

17. The Energy Efficiency of Italian firms Firm-level data on investments in EE • Ex-ante what are the factors influencing investments in EE? • Energy costs incidence and dynamics (+ expectations on energy prices) • Incentives • Financial resources • Innovation and productivity (bi-directional link)

18. The Energy Efficiency of Italian firms Firm-level data on investments in EE • ENERGY COSTS. Using data at sector-level+class size on energy purchases of Industrial Firms (warning: difficult to disentangle Dp and Dq; reverse causality Dq si correlated with INV EE)

19. The Energy Efficiency of Italian firms Firm-level data on investments in EE • ENERGY COSTS PREVALENCE. Dividing data at sector-level+class size on energy purchases of Industrial Firms by the corresponding turnover

20. The Energy Efficiency of Italian firms Firm-level data on investments in EE • DEGREE OF COMPETITION. Share of the turnover from sales abroad.

21. The Energy Efficiency of Italian firms Firm-level data on investments in EE • FISCAL INCENTIVES. Only to be completed by firms that made investments to improve energy efficiency in 2008 or in 2009: would have made this expenditure even in the absence of government incentives provided by the recent financial laws?

22. The Energy Efficiency of Italian firms Firm-level data on investments in EE • FINANCIAL CONSTRAINTS. Would the firm be willing, at present, to pay a slightly higher rate of interest or accept worse terms (e.g. higher collateral) in order to borrow more?

23. The Energy Efficiency of Italian firms Firm-level data on investments in EE • INNOVATION. Expenditure on R&D and market research; design and test (2009)

24. The Energy Efficiency of Italian firms Firm-level data on investments in EE • PRODUCTIVITY. Ratio of turnover to number of employees (2008)

25. The Energy Efficiency of Italian firms Firm-level data on investments in EE

26. The Energy Efficiency of Italian firms From description to explanation: a model of the investments in EE • A “Hurdle model” is adopted to model investment in energy efficiency: the decision to invest in energy efficiency is modeled separately from the amount invested. • Outcome variable in stage 1: D(INV in EE>0) in stage 2: ln(INV in EE/Employee) • The controls used in the two regression are information on firm structure (employees, turnover, sector, ..), and the factors considered in the descriptive analysis (financial constraints, energy costs, incentives to EE, innovation, competition, productivity).

27. The Energy Efficiency of Italian firms Estimated on the subsample of firms with incentives=1 Results: the decision to invest Outcome variable: D(INV in EE>0) Average marginal effects Number of obs = 1320 ------------------------------------------------------------------------------ | Delta-method | dy/dx Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- empl>100 | .10246 .0331615 3.09 0.002 .0374646 .1674555 south | -.2673742 .0421925 -6.34 0.000 -.35007 -.1846783 basic_metals | -.0826453 .0391519 -2.11 0.035 -.1593817 -.0059089 textiles | -.102821 .0578435 -1.78 0.075 -.2161922 .0105502 costhigh | .0317508 .0391415 0.81 0.417 -.0449652 .1084668 dcost | -.0339359 .0436879 -0.78 0.437 -.1195625 .0516907 listed | .1449335 .1166868 1.24 0.214 -.0837684 .3736355 liq_constr | -.0159131 .0507096 -0.31 0.754 -.1153022 .083476 innovation | .0701248 .0397167 1.77 0.077 -.0077184 .147968 productivity | .042042 .0379741 1.11 0.268 -.0323859 .1164698 ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ | Delta-method | dy/dx Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- empl>100 | .3877527 .1870429 2.07 0.038 .0211555 .75435 liq_constr | -.4285686 .2147726 -2.00 0.046 -.8495152 -.0076219 ------------------------------------------------------------------------------

28. The Energy Efficiency of Italian firms Results: the amount invested Outcome variable: ln[(INV in EE)/Employee)]

29. The Energy Efficiency of Italian firms Results: the amount invested Outcome variable: ln[(INV in EE)/Employee)] Linear regression Number of obs = 391 F( 9, 381) = 15.37 Prob > F = 0.0000 R-squared = 0.2556 Root MSE = 1.1152 ------------------------------------------------------------------------------ | Robust linveffadd | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- empl>100 | -1.118129 .1578535 -7.08 0.000 -1.428502 -.8077558 south | -.7845119 .2203781 -3.56 0.000 -1.217822 -.3512022 basic_metals | -.3464468 .1539742 -2.25 0.025 -.6491924 -.0437012 textiles | -1.125793 .2937513 -3.83 0.000 -1.70337 -.5482168 costhigh | .05772 .1528207 0.38 0.706 -.2427575 .3581975 dcost | -.2295049 .2137149 -1.07 0.284 -.6497132 .1907034 listed | .445117 .1887972 2.36 0.019 .0739021 .8163318 liq_constr | .0573385 .1827736 0.31 0.754 -.3020328 .4167098 innovation | -.3006026 .1747644 -1.72 0.086 -.6442261 .0430208 productivity | .0546945 .167141 0.33 0.744 -.2739425 .3833314 _cons | .0414844 .1348963 0.31 0.759 -.22375 .3067188 ------------------------------------------------------------------------------

30. The Energy Efficiency of Italian firms Results: the amount invested Outcome variable: ln[(INV in EE)/Employee)] Linear regression Number of obs = 186 F( 11, 174) = 3.90 Prob > F = 0.0000 R-squared = 0.2015 Root MSE = 1.3082 ------------------------------------------------------------------------------ | Robust linveffadd | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- empl>100 | -.7295851 .2522424 -2.89 0.004 -1.227434 -.2317364 south | -.5465285 .2706474 -2.02 0.045 -1.080703 -.012354 basic_metals | -.2932994 .2946285 -1.00 0.321 -.8748052 .2882064 textiles | -.5526201 .3458656 -1.60 0.112 -1.235252 .130012 costhigh | .4907427 .2306101 2.13 0.035 .0355895 .9458959 dcost | .1631447 .2906903 0.56 0.575 -.4105882 .7368777 listed | .3643659 .6960768 0.52 0.601 -1.009475 1.738207 liq_constr | -.1639417 .2753511 -0.60 0.552 -.7073999 .3795164 incentives | .5031161 .3008957 1.67 0.096 -.0907591 1.096991 innovation | -.1789353 .2695632 -0.66 0.508 -.7109698 .3530993 productivity | .6358224 .2585559 2.46 0.015 .1255129 1.146132 _cons | -1.23964 .3220934 -3.85 0.000 -1.875352 -.6039266

31. The Energy Efficiency of Italian firms Conclusions 1 (positive) • The determinants to invest or not in energy efficiency are mainly related to firms’ size (distribution of the fixed costs), sector, geographic location. Innovative firms show an higher propnesity to invest in EE. Firms that made the investment only because of fiscal rebates result resource-constrained. • The amount of the investment per employee is negatively related to firm size. It is higher for firms with an higher incidence of energy costs and listed (less resource constrained). It is lower for the firms in the South and those that invest more in R&D (resource competitions among different project?). The incentives have a positive effect on the amount invested.

32. The Energy Efficiency of Italian firms Conclusions 2 (normative) • Policy incentives to promote EE are homogeneous both at the industry and firm level. The empirical evidence reveals, however, that these measures have differential effects with respect to various industries and firm size. • For EE – as for innovation in general - “size matters”. Italian firms are small and face high and possibly increasing energy prices (e.g. due to RES-E financing). Fiscal rebate appears an effective tool to induce firms to invest in EE. It is not clear if it is also efficient (the cost of the fiscal rebates covers the “public good” provision of an improved EE?).

33. The Energy Efficiency of Italian firms THANKS!

34. The Energy Efficiency of Italian firms Energy industrial use in the EU Characteristics of final energy consumption in the industrial sector of the EU-27 (IEEA, 2009): • final energy demand has been stagnating at around 320 Mtoe for the last 15 years; • at EU-27 level, the industrial sector represents 27 per cent of the final consumption in 2007, from 33 in 1990; • variations observed were mainly due to business cycles; • since 2006 energy prices went up; however, due to time lags in measures taken to cope with high prices and the recent drop of energy prices since 2008 the impact of higher energy prices on final energy consumption is not visible yet.

35. The Energy Efficiency of Italian firms Source: Odysee. Energy industrial use in Italy Energy efficiency index(index 2000=100)

36. The Energy Efficiency of Italian firms Energy industrial use: cross cutting tech’s Source: IEEA (2009), “Energy Efficiency Trends and Policies in the Industrial Sector in the EU-27”.

37. The Energy Efficiency of Italian firms Energy industrial fuel mix: Italy and EU Italy EU27 Source: Our computations on Eurostat data.

38. The Energy Efficiency of Italian firms Barrier Examples Market  Market organisation and price distortions prevent customers from appraising the true value of EE. Split incentive problems created when investors cannot capture the benefits of improved efficiency.  Transaction costs (project development costs are high relative to energy savings). Financial  Up-front costs and dispersed benefits discourage investors  Perception of EE investments as complicated and risky, with high transaction costs  Lack of awareness of financial benefits on the part of financial institutions. Information  Lack of sufficient information and understanding to make rational investment decisions. Regulatory  Energy tariffs that discourage EE investment (such as declining block prices).  Incentive structures encourage energy providers to sell energy rather than invest in cost-effective EE.  Institutional bias towards supply-side investments. Technical  Lack of affordable EE technologies suitable to local conditions.  Insufficient capacity to identify, develop, implement and maintain EE investments Source: IEA (2010), “Energy Efficiency Governance: Handbook”. The barriers to EE