metadata: authors: 0: author: Sahin,Sebnem
count: Türkiye
docna: 0: docna: Firm-level decomposition of energy
            consumption in Turkish manufacturing industry
docty: Policy Research Working Paper
subtopic: Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Energy Consumption,Energy Conservation & Efficiency,International Trade and Trade Rules,Environment and Energy Efficiency,Energy Demand,Energy and Environment,Energy and Mining,Business Cycles and Stabilization Policies
abstracts: cdata!: Energy efficiency in industry is a
            crucial topic for Turkey, as the country has an import
            dependency of 80 percent in energy. Although the importance
            of enhancing energy efficiency in industry is widely
            acknowledged, there has not been any study examining the
            energy efficiency in Turkish industry at micro level.
            Employing a sound decomposition methodology on a firm-level
            data set of manufacturing firms, this paper documents that
            there was a significant decrease in the energy intensity of
            firms over 2005-12. In contrast, structural change across
            manufacturing sectors and across firms within sectors had
            positive but limited effects on the overall energy
            efficiency over the period.
geo_reg_key: 517191,119229,517198,517208
repnme: repnme: Firm-level decomposition of energy
            consumption in Turkish manufacturing industry
display_title: Firm-level decomposition of energy
            consumption in Turkish manufacturing industry
listing_relative_url: /research/2017/10/28027356/firm-level-decomposition-energy-consumption-turkish-manufacturing-industry
topicv3: Manufacturing Sectors m1326521 1281,Energy and Extractives m1326595 507,Energy Efficiency in Industry m1326602 538,Energy Efficiency m1326852 533,Trade m1326924 698
publishtoextweb_dt: 2017-10-04T00:00:00Z
no_of_pages: 23
author_keys: 0: author_key: 888050
model_extractions: WPS8211 Policy Research Working Paper 8211 Firm-Level Decomposition of Energy Consumption in Turkish Manufacturing _Sebnem Sahin_ Development Research Group Environment and Energy Team October 2017
Policy Research Working Paper 8211

# **Abstract**

Energy efficiency in industry is a crucial topic for Turkey, as the country has an import dependency of 80 percent in energy. Although the importance of enhancing energy efficiency in industry is widely acknowledged, there has not been any study examining the energy efficiency in Turkish industry at micro level. Employing a sound decomposition methodology on a firm-level data set of manufacturing firms, this paper documents that there was a significant decrease in the energy intensity of firms over 2005–12. In contrast, structural change across manufacturing sectors and across firms within sectors had positive but limited effects on the overall energy efficiency over the period.

This paper is a product of the Environment and Energy Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at ssahin@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Firm-Level Decomposition of Energy Consumption in Turkish Manufacturing Industry**<sup>**#**</sup>

**Sebnem Sahin**<sup></sup>

**JEL Classifications:** O13, O14, Q55 **Keywords:** Energy intensity; Turkish manufacturing. **Sectors:** Energy, Environment

> # I acknowledge the generous financial support from the World Bank research support budget. The findings expressed in this paper are those of the authors and do not necessarily represent the views of the World Bank. I thank an anonymous reviewer for very useful comments on an earlier draft of the paper.

>  Senior Environmental Economist at the World Bank. Author can be contacted at ssahin@worldbank.org.
# **I. INTRODUCTION**

Energy efficiency in industry is a crucial topic for Turkey. The country has a structural trade deficit, which in some years in the last two decades reached as much as 9% of its GDP<sup>1</sup> . Among the contributors of the trade deficit, oil and natural gas imports have the lion’s share. Having an import dependency of around 80% in energy, US$55 billion of a total of US$84 billion trade deficit in 2014 was due to energy imports (Turkstat). A significant factor underlying such a high energy dependency is that Turkey’s manufacturing industry is relatively energy intensive. While every US$1,000 of GDP requires 0.18 ton of oil equivalent (toe) energy consumption in the OECD, it takes 0.26 toe in Turkey (WB, 2012). Therefore, there is large room for and great benefits associated with policy effort to increase energy efficiency in Turkish manufacturing industry.

The importance of energy efficiency is recognized by both the Turkish government and the World Bank. The 2012-2014 Medium-Term Program of the government states that “...The systematic pursuit of energy efficiency is therefore a priority and critical for Turkey’s energy security, macro/fiscal stability, competitiveness, climate change mitigation and environmental sustainability...” (Ministry of Development, 2012). Identifying the energy efficiency one of the priority areas the Country Partnership Strategy, the World Bank considers greater energy efficiency and diversification of energy sources keys to reducing Turkey’s reliance on external finance (WB, 1012).

Although the energy inefficiency problem in Turkey is broadly acknowledged, there is a lack of credible studies to be consulted for designing policies aiming at increasing energy efficiency in the country. This is particularly a problem for energy use in industry, which accounted for 33.5% of total final energy use in Turkey in 2014 (GDEA)<sup>2</sup> . Being one of a few studies on the topic, Turkay et al. (2012) compares sectors by their share of energy consumption in total manufacturing costs. The study lists a long series of recommendations to increase energy efficiency in manufacturing facilities. The World Bank report (2015), on the other hand, outlines an institutional and legal framework to enhance energy efficiency in Turkey.

> 1 In fact, the unsustainable current account deficit was the main reason for severe financial crises in the country in 1994 and 2001.

> 2 Shares of other areas of energy use are as follows: Residential, commercial and public buildings (35%), transportation (29%), and agricultural production (2%).

2
Motivated by the importance of energy efficiency for Turkey, the lack of credible studies in this area and the existence of a unique firm-level data set that covers all manufacturing industry over the 2005-2012 period, this study aims to understand how energy efficiency evolved in Turkish manufacturing industry by its components.

Implementing a decomposition analysis, specifically, this study examines the roles of:

- Change in energy intensity of firms (technical efficiency, firm intensity effect),

- Shift of production across firms in the same sub-sector (within sector reallocation - firm structural effect),

- Shift of production across sub-sectors (across sector reallocation – sector structural effect)

- Production change (activity effect)

in the change in energy consumption of Turkish manufacturing industry over 2005-2012.

The first and second components above can be calculated only by using firm level data. To our knowledge, there is only one study (Petrick, 2015) that used a firm level data set (for Germany) and investigated these two components in the literature. Moreover, to our knowledge, this is the first decomposition analysis for Turkish manufacturing industry in the literature.

Findings in this paper are expected to provide useful insights to design more effective and focused policies to increase energy efficiency in Turkish manufacturing. Therefore, the study aims to indirectly serve to policies for more favorable external balances and better climate results of the energy consumption in the country.

The organization of the paper is as follows: The second section discusses the literature. The third section describes the data set and provides several preliminary figures. The fourth section introduces the firm level decomposition methodology. The fifth section presents the decomposition findings. Finally, the sixth section discusses the findings.

# **II. LITERATURE**

Since their first application in late 1970s, index decomposition analyses have been increasingly used to study the impacts of structural change (i.e. changes in industry product mix) and sectoral energy intensity change in the energy economics literature. They are also widely used by national energy institutions around the world for policy-making purposes.

3
Decomposition methods can be broadly categorized in two groups: methods based on the Laspeyres index and methods based on the Divisia index.

Employing a Laspeyres index based decomposition, Jenne and Cattell (1983) report that during 1973-1982, structural change accounted for half of the 18% decrease in energy intensity of UK industry. The remaining residual of 9% implies a 1% annual improvement in energy efficiency. Following a similar methodology, Marlay (1984) finds that part of the reduction in the energy consumption of US industry over 1973-1983 resulted from improvements in the efficiency of industrial process technologies. Most is attributed, however, to slower growth in industrial economic activity and unprecedented changes in the composition of industrial output away from industries that consume large amounts of energy.

In another study, Howarth et al. (1991) examine trends in manufacturing energy use in eight OECD countries, decomposing the changes that occurred between 1973 and 1987 into the effects of changes in aggregate manufacturing activity, industry structure and energy intensities measured at the industry level. They conclude that structural change led to modest reductions in most countries studied.

Underlining theoretical weaknesses of decompositions based on the Laspeyres index, Boyd et al. (1987) propose the Divisia index approach as an alternative to the Laspeyres in energy decomposition analysis. They present substantial empirical support for the hypothesis that sectoral shift in manufacturing production is an important factor in explaining changes in energy intensity. Moreover, Boyd et al. (1988) make some comparisons between energy intensity decomposition and the formulation of economic indices. They illustrate the useful properties of the Divisia index in performing energy intensity decomposition.

Thereafter, extensions and refinement of methods based on the Divisia index were made. Liu et al. (1992) develop two general parametric Divisia index methods. They also extend the Divisia based index methodology to the environment field. To overcome the two commonly encountered problems - existence of a residual after decomposition and the handling of the value zero - with the existing Divisia index based decompositions; Ang and Choi (1997) modify the Divisia index decomposition method by replacing the arithmetic mean weight function by a logarithmic one. This transforms the Divisia index method into a perfect decomposition with no residual. The Logarithmic Mean Divisia Index decomposition is formalized by Ang and Liu (2001) in multiplicative form.

As for empirical applications of decompositions based on the Divisia index, to decompose the reduction in energy intensity in China between 1978 and 1995 into technical change and 4
various types of structural change, Garbaccio et al. (1999) employ input-output tables. They conclude that between 1987 and 1992, technical change within sectors accounted for most of the fall in the energy output ratio and structural change actually increased the use of energy. An increase in the import of some energy-intensive products also contributed to the decline in energy intensity.

Greening et al. (1998) apply the Adaptive Weighted Divisia rolling base year index to total carbon emissions from the manufacturing sector of 10 OECD countries for the period 1971– 1991. They find that declines in aggregate carbon intensity for these countries may be primarily attributed to decreases in energy intensity, i.e. increases in the average factor productivity of energy.

Using data of 2,582 large and medium-size Chinese enterprises over the period 1997-1999 and employing the multiplicative Divisia index, Fisher-Vanden et al. (2004) decompose the intensity of three types of energy – coal, refined oil, and electricity into the contributions of sectoral shift (i.e., changes in the sectoral composition of total industrial output) and subsector productivity change (i.e. changes in energy intensity within individual industrial sectors). They document that while subsector productivity change emerges as the dominant factor driving declines in oil and electricity intensities, sectoral shift plays a near equal role in declining coal and refined oil intensities.

Applying logarithmic mean Divisia index (LMDI) techniques, Ma et al. (2008) investigate the role of inter-fuel substitution in the decline in energy intensity or the causes of the rise in energy intensity in the period 1980-2003 for Chinese manufacturing industry. They find that technological change is the dominant contributor to the decline in energy intensity and structural change at the industry and sector (sub-industry) levels actually increased energy intensity over the period. On the other hand, structural change involving shifts of production between sub-sectors decreased overall energy intensity with inter-fuel substitution contributing little to the changes in energy intensity<sup>3</sup> .

Finally, being the only firm level study in the literature, Petrick (2015) decomposes changes in total CO2 emissions in German manufacturing industry to changes in activity level, structural change between sectors, shifting market shares within sectors, energy intensity at the firm level, fuel mix, and emission factors, applying an LMDI index decomposition technique. He reveals that shifts in production across firms in manufacturing sub-sectors and shift of production across sub-sectors play larger roles in determining the path of energy use

> 3 Please see Liu and Ang (2007) and Ang (2015) for a detailed review of the related literature.

5
in German manufacturing industry over the 1995-2007 period than the change in firm energy intensity does.

Although there has been no attempt so far to decompose energy consumption/CO2 emissions in the Turkish economy by using firm level data in the literature, there are several papers that covered the topic for Turkey by employing data at more aggregated levels. Following the LMDI methodology, Turut Asik et al. (2008) reveal that the main cause of the change in the energy intensity in Turkish manufacturing intensity over the 1992-2001 period is change in the energy intensity at the sub-sector (industries at 4 digits) level instead of a structural effect, i.e. production shift, across sub-sectors. In another study, Tunc et al. (2009) document that over the 1970-2006 period, economic activity was the main component that determined the changes in CO2 emissions in Turkey. Moreover, the sectoral intensity effect had a significant role in the CO2 change, unlike the sectoral structural effect.

Employing a refined Laspeyres methodology, Kumbaroglu (2011) show for the 1990-2007 period that the energy intensity effect has a dominant impact on CO2 emissions in Turkish manufacturing industry. Applying the LMDI methodology on a Turkish manufacturing industry data set at the ISIC 4-digit level, Yilmaz et al. (2016) document that the activity effect was by far the most contributing effect in the increase in energy consumption in Turkish manufacturing industry over the 1981-2011 period. The structural effect had a slightly negative effect and the intensity effect had a slightly positive impact on energy consumption during the period.

# **III. DATA SET AND PRELIMINARY ANALYSIS**

This study makes use of Annual Industry and Services Surveys (AISS) of the Turkstat for the 2005-2012 period. AISS is divided into two parts, based on firm employment size: (i) a census of firms with at least 20 employees in that year and (ii) a large sample of firms with fewer than 20 employees with sampling based on region and NACE 4-digit sector.

The variables used for this study are:

- Firm random codes to identify firms (codes change across firms in a year but are the same over time for the same firm),

- Year and 2-digit NACE sector codes,

- Value of energy consumption,

- Value of production (gross output).

6
In order to prepare the data set for computations, monetary variables were deflated by applying sector level wholesale price indices and energy price indices. Table 1 below presents some annual key figures from the data set. The figures are consistent with those officially announced by Turkstat.

**Table 1: Key Figures of the Turkish Manufacturing Industry over Time (All Firms)**

|**Period**|**Number of**<br>**Establishments**<br>**(1,000x)**|**Employment**<br>**(million)**|**Energy**<br>**Consumption**<br>**(2005 billion TL)**|**Value of**<br>**Production**<br>**(2005 billion TL)**|
|---|---|---|---|---|
|2005|302|2.58|11.4|322|
|2006|310|2.68|12.9|359|
|2007|317|2.78|14.0|372|
|2008|322|2.78|13.4|392|
|2009|325|2.50|11.6|350|
|2010|300|2.79|12.8|415|
|2011|333|3.08|14.0|488|
|2012|310|3.32|14.6|495|
|Average|315|2.25|13.1|399|

Since we can properly track only firms that employ 20+ employees every year within the period (due to the fact that firms with fewer than 20 employees are not subject to the census sample), we have to limit the firm level decomposition to firms existing in the data set every year over the period. The number of these firms (all period 20+ firms) is 9,379. Although they represent a very small share of all firms by count (3%), their average shares over the 20052012 period in total manufacturing employment, energy consumption and production are 45.6%, 72.5% and 66.5%, respectively. (Corresponding figures of 20+ firms and those of 9,379 all period 20+ firms are provided in the Appendix.) Next, we provide sector level statistics in the following three figures. First, Figure 1 provides an Index that compares total energy consumption of sectors in 2005 and 2012 and also shows how energy consumption of each sector changed over the 2005-2012 period. In the figure, the total energy consumption of all sectors is set to 100. The total of all sectors in 2012 is computed as 127.8, indicating a 27.8% increase in the total energy consumption of the manufacturing industry over the 2005-2012 period. (This can be verified in Table 1 as well.) As for sectors, classified by NACE (rev.1.1) 2-digit sectors, other non-metallic mineral products (cement, glasses, ceramics etc.) manufacturing, textile manufacturing and basic metals manufacturing were leading sectors in terms of energy consumption with a total share of 56% 7
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LMDI-I has all the desirable properties of perfect decomposition and consistency in aggregation. Perfect decomposition ensures that the decomposition results obtained do not contain a residual term<sup>7</sup> .

Adapting the Log-Mean Divisia Index-I decomposition, originally developed for sector level analysis, to firm level data, the general formula of our decomposition methodology becomes the following<sup>8</sup> : where s, f, E and Q stand for sector, firm, energy consumption and production, respectively.

Then, change in the energy consumption of the manufacturing industry between the base year (<sup>0</sup> ) and the end year (<sup>T</sup> ) can be decomposed into components as follows: In the equation above:

- Dman is the total change in the energy consumption in the manufacturing industry,

- Dact is the activity effect, the change in the aggregate associated with a change in the overall level of the activity in the manufacturing industry,

- Dstrs is the sector structural effect, the change in the aggregate associated with a change in the relative shares of sectors in overall manufacturing,

- Dstrf is the firm structural effect, the change in the aggregate associated with changes in the relative shares of firms within sectors,

- Dintf is the intensity effect, the change in the aggregate associated with changes in the firm energy intensities.

> 7 See Ang (2004, 2015) for a detailed comparison of different decomposition methods.

> 8 For the mathematical derivation of the formula please see Ang and Liu (2001).

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Formula to compute components of decomposition are as follows: where the weight of each firm is computed as:

# **V. DECOMPOSITION RESULTS**

Firm level decomposition results are provided in Figures 4 to 8. Over the 2005-2012 period, energy consumption in Turkish manufacturing industry increased by 27.3% (Figure 4). Out of 7 years covered, energy consumption decreased only in 2008 and 2009, by 2.8% and 12.9%, respectively. This is not surprising because the Turkish economy contracted in the Q4 of 2008 and the whole 2009 in parallel to the global economic crisis.

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<!-- Start of picture text --> 15 140<br>127.3 130<br>4 119.2 —<br>1 120<br>5<br>04.1 110<br>0 100<br><!-- End of picture text --> <!-- Start of picture text --> 15 140<br>127.3 130<br>4 119.2 —<br>1 120<br>5<br>04.1 110<br>0 100<br>2006 2007 2010 2011 2012<br>-2.8 90<br>+5<br>80<br>-10 7<br>70<br>-15 60<br>Mm" yro¥ % change tr Index (2005-100)<br>18 150.4 453.3 [ 160<br>12 140<br>126.3<br>. 119.5 418, a<br>0.5<br>° 100<br>2006 2007 2008 2010 2011 2012<br>6 - 80<br>12 60<br>-18 40<br>"=" YtoY YtoY % change & index (2005-100)<br><!-- End of picture text --> <!-- Start of picture text --> 2006 2007 2008 2010 2011 2012<br>6 - 80<br>12 60<br>-18 40<br>"=" YtoY YtoY % change & index (2005-100)<br><!-- End of picture text -->
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# **_Effect of Firm Selection on Firm Level Decomposition Findings_**

Remember that for conducting firm level analysis we had to work only with 9,379 specific firms that exist every year over the 2005-2012 period. One consideration pertaining to the firm level decomposition findings is the degree to which they are representative of the energy patterns of the whole manufacturing industry. Since these firms account for 72.5% of energy consumption and 66.5% of production the manufacturing industry, we do not expect firm selection has a significant negative impact on the quality of our findings above. However, in order to get an educated idea about this, we below run traditional sector level decomposition by first using the whole universe of firms and second by using only those specific 9,379 firms<sup>9</sup> .

The decomposition findings presented in Table 2a and Table 2b are very similar. Therefore, we conclude that not being able to cover all firms in the firm level decomposition does not pose a big problem for the representativeness of that decomposition of the whole manufacturing industry.

**Table 2a: Decomposition Results at Sector Level for the 2005-2012 Period (including all firms)**

|**Dman**|**Dact**|**Dstrs**|**Dints**|
|---|---|---|---|
|1.278|1.538|0.981|0.847|

**Table 2b: Decomposition Results at Sector Level for 2005-2012 Period (including only 9,379 firms existing in the data set over the whole period)**

|**Dman**|**Dact**|**Dstrs**|**Dints**|
|---|---|---|---|
|1.273|1.520|0.971|0.862|

# **VI. DISCUSSION OF FINDINGS**

In this section, we first discuss our firm level decomposition findings by comparing with the findings of the only firm level study in the literature - Petrick (2015) for the German manufacturing industry. Although the time period of that study is different from ours, we still conduct such a comparison as it is the only firm level decomposition analysis in the literature and we believe that energy dynamics in an industry is not likely to change significantly over a short period of time. Comparison by each decomposition component is given in Table 3. First, unlike a significant 27% increase in the energy consumption in Turkey over the 2005-2012 period, energy consumption in Germany increased by a much smaller amount (5%) over the 2000-2007 period.

> 9 We use the multiplicative version of the Log-Mean Divisia Index Method-I decomposition introduced by Ang and Liu (2001).

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**Table 3: Comparison of Turkey and Germany Findings**

||**Turkey (2005-2012)**|**Germany (2000-2007)**|
|---|---|---|
|Activity Effect|51%|15%|
|Sectoral Structural Effect|-2%|-6%|
|Firm Structural Effect|-2%|-4%|
|Intensity Effect|-13%|1%|
|_Aggregate Energy Consumption_<sup>**10**</sup>|_27%_|_5%_|

Second, although their magnitudes by country differ significantly, the activity effect has been the main driver of the change in aggregate energy consumption in both countries with 51% for Turkey and 15% for Germany. Third, both the sectoral structural effect and the firm structural effect had a more contractionary effect on aggregate energy consumption for Germany (-6% and -4%, respectively) than for Turkey (-2% for both effects). This implies that, although across-sector and across-firm within-sector production reallocation has been towards energy efficient sectors/firms in both Germany and Turkey, these effects were much stronger in Germany. Finally, while the energy intensity effect for Germany was almost stagnant over 2000-2007 with a mere 1% increase, the energy intensity of a specific firm decreased by on average an impressive 13% over the 2005-2012 period.

To recap, using a firm level decomposition methodology, we documented that, rather than across sectors structural change, and within sector across-firm structural change, the activity effect and the firm intensity effect were the drivers of the change in energy consumption in Turkish manufacturing industry over the 2005-2012 period. With the superiority of firm level analysis over sector level analysis, we could show in this study that the energy efficiency increases within sectors seen in Table 2a and Table 2b are from the increase in firm level efficiency rather than shift of production towards more energy efficient firms within sectors.

As for policy implications, we believe that there are two areas that need to be investigated further for designing policies aiming at higher energy efficiency in Turkey. First, the very small role of the production shift from higher energy intensive sectors to lower energy intensive sectors (sector structural effect) as well as from higher energy intensive firms to lower energy intensive firms within-sectors (firm structural effect) might be indicating serious market failures and barriers that prevent more energy efficient firms from increasing their share in total production in Turkish manufacturing industry. Therefore, addressing the source of this low-level dynamism could yield useful results for enhancing energy efficiency.

> 10 In Petrick (2015), the aggregate CO2 emissions is decomposed, instead of the aggregate energy consumption. We calculated aggregate energy consumption for that study by deducting the effects of fuel mix change and emission factor of fuels from the aggregate CO2 emissions presented in that study.

17
Second, and in contrast to the structural change, the significant decrease in the firm level energy intensity over the 2005-2012 period can be considered an impressive progress towards energy efficiency in the manufacturing industry. Although there are several potential candidates as the source of this progress such as increasing openness to trade and technological development<sup>11</sup> , exact reasons can only be revealed by research designed and conducted solely for this purpose.

> 11 See for example Fisher Vanden et al. (2013) for the reasons behind the energy intensity decrease in some industries in China.

18