Does Plant Ownership Affect The Level Of Pollution Abatement Expenditure

Does Plant Ownership Affect The Level Of Pollution Abatement Expenditure? Alan Collins Department of Economics, University of Portsmouth, Locksway Road, Milton, Southsea, Hampshire, PO4 8JF, U.K Email: alan.collins@port.ac.uk Richard I.D.Harris Department of Economics and Finance University of Durham, UK Abstract This paper considers a number of hypotheses Primarily amongst them is the notion that foreign owned plants spend more on pollution abatement than domestically owned plants after controlling for productive efficiency and cognisant of the prevailing regulatory regime The evidence drawn upon in the first econometric assessment of this contention is plant level data from the UK metal manufacturing industry In essence, this study directly estimates the influence of ownership and efficiency characteristics in firms’ decisions regarding whether to spend or not on pollution control and how much to spend To explore these themes a two stage econometric exercise was undertaken on a hitherto unused source of environmental data, namely the UK Annual Business Inquiry Respondents Database (or ARD) A Heckman-type sample selection model was estimated to examine the probability of abatement expenditure being made or not and also to explain how much was spent on each of the principal means of pollution control The results suggest that older plants were more likely not to incur any expenditure on process or post-production pollution capital expenditure Plants that were non-EU foreign owned were generally more likely to spend on pollution abatement than UK plants Likewise, in the main, the more efficient firms and the more capital-intensive firms were also more likely to spend on pollution control than UK-owned firms The significance or otherwise of a wide range of other factors was also explored and reported on JEL-L JEL-O JEL-D Keywords Pollution abatement Efficiency UK manufacturing a Support from the Economic and Social Research Council (reference no R000222602) is gratefully acknowledged, as is permission from the Office for National Statistics at Newport, South Wales, to use the Annual Business Inquiry Respondents Database I Introduction An extensive body of theoretical studies continues to evolve and shed light on firms’ likely responses to alternative environmental regulatory instruments and regimes1 An interesting recent strand of this work has begun to examine in particular firms’ technology choice with respect to the linkages between profit maximisation and the imposition of specific pollution abatement instruments (Kort et al 1991) This is an important policy focus for regulators and the business community in the context of increasingly aggressive environmental policy objectives, where the scope for policy substitution has been raised This relates to the idea that environmental policy objectives may be attained by (i) pure productive efficiency enhancing means and (ii) direct pollution abatement enhancing means It may be, however, as in the U.K and elsewhere, that environmental regulatory bodies not have as yet the human capital resources to contemplate the environmental potential of the productive efficiency enhancing means In the context of the USA Gray and Shadbegian (1995) found a negative relationship between a plant’s pollution abatement costs and its total factor productivity Yet, it is reasonable to posit that more efficient plants may have less need to engage in pollution abatement expenditure (PAE), since, by virtue of their greater efficiency with regard to the use of resource inputs, they intrinsically generate lower levels of pollution Perhaps contrarily, it is also reasonable to think that efficient plants will be amongst the most keen to seize worthwhile resource input minimizing opportunities when they arise Clearly, this is likely to be associated with higher levels of some particular types of PAE, such as process-based capital expenditure, as opposed to arguably cruder end-of-pipe solutions Despite the extensive theoretical activity in this area, relatively little econometric work has taken place that moves us towards injecting more of an empirical dimension in support of this developing firm-environment literature The non-case study based empirical work that has taken place has primarily focused on evidence drawn from the USA Such work has usefully exploited the annual Pollution Abatement Costs and Expenditures Survey (Barbera and McConnell 1986) Whilst metals have recently been the subject of macro-scale environment-economy interaction modelling (Guinee et al 1999), this particular study contributes to the corpus of firm-environment research at the industry level This work empirically examines the linkages between plant ownership, productive efficiency and the decision to engage in pollution abatement More specifically, we address the following question See, for example Cornwell and Costanza (1994), Laffont and Tirole (1994, 1996), Damania (1996), Jung et al (1996), Fredriksson (1998), Goulder et al (1999), Schwabe (1999), Baudry (2000) After controlling for differences in productive efficiency, domestic or foreign-owned plants spend more on pollution abatement? Evidence is drawn from the specific context of the UK metal manufacturing industry over the period 1991-1994 Other UK industries over this time period would have presented equally satisfactory sources of evidence to explore the hypotheses we set out, operating as they did under the same environmental regulatory regime Using this evidence, for those plants found to be engaging in pollution abatement, this study also presents the first econometric study to consider what determines their actual level of PAE in the four main categories of pollution control These are, namely, process based capital expenditure, post-production capital expenditure (end-of-pipe solutions), current expenditure (using the firm’s own staff), and through payments to others (i.e contracting out some pollution control functions) Yet, as we have already emphasised, plausible reasoning could readily be devised to articulate both positive and negative influences of productive efficiency on the undertaking of PAE This paper extends the firm-environment literature in two key aspects First, we believe our study provides the first non-US econometric study of PAE relevant to a major pollution intensive industry This is furnished by exploitation, for the first time by economists, of the environmental data contained within the Annual Business Inquiry Respondents Database (ARD) of the UK Annual Census of Production (now known as the Annual Business Inquiry) Second, this study is the first to explicitly consider the hypothesis that foreign plant ownership raises the probability that a plant will engage in pollution abatement activity Many studies have investigated or hypothesised how national or cultural differences may influence firm profitability, productivity, and levels of research and development amongst other things2 Hence, there might also reasonably be expected to feature some environmental performance implications arising from such differences For example, given that the stringency of environmental regulatory regimes varies significantly in different countries one might expect there to be environmental benefits aspects to the positive externalities generally said to arise from the presence of foreign -owned (FO) plants in a particular host country (Blomstrom and Kokko 1998) Indeed there is a large body of work3 that has sought to suggest, identify and help explain a wide range of positive See, for example, Dunning (1958, 1977), Vernon (1966, 1979), Kindleberger (1969), Caves (1974), Johnson (1970,1975) Hymer (1976), Buckley (1983) See, for example, Globerman (1979), Krugman (1991ab), Grossman and Helpman (1991), Venables (1994), Edwards (1998), Aghion and Howitt (1998) effects on industry-wide or general manufacturing sector productivity, as a direct consequence of such increasing FO firm penetration The principal findings of this particular study are that increasing efficiency levels leads to a small increase in the probability of making expenditures on pollution abatement investment in the production process but very substantially increases the probability of zero expenditure on direct staff and operating costs relating to pollution control It is also found that US-owned plants are more likely to incur some spending on post-production assets but are significantly less likely to spend on other forms of pollution control EU-owned plants, however, are more likely to spend on pollution abatement than UK plants Plants owned by enterprises from Australia, New Zealand, South Africa and Canada have a higher probability of incurring some expenditure on pollution abatement Furthermore, and probably reflecting actual or perceived variations in regulatory enforcement effort, plants in less populated areas are far more likely not to engage in any PAEs The paper is organized in the following way In Section II theoretical issues are considered relevant to the linkages between ownership status, efficiency and the regulatory regime in the time period under study, and our main hypotheses are posited Section III presents some background contextual information relating to the UK metal manufacturing industry over this period This descriptive analysis suggests a number of hypotheses that are tested in the subsequent econometric phase of the study Section IV sketches an outline of the modelling strategy and econometric model employed to examine the influence of productive efficiency and ownership status on PAE Section V presents the results with brief concluding remarks offered in Section VI II Ownership, Efficiency and Capital Intensity with Technology-Forcing Environmental Standards There are a number of theoretical reasons why one might expect differences between domestically and foreign owned plants with respect to their level of efficiency and accordingly their environmental performance These relate to mainstream productive efficiency reasons and more specific resource productivity based explanations These are considered in turn Irrespective of the fact that FO-plants are more likely to be younger, explanations for higher FO plant productivity (as in Figure 1) relates to a combination of two sources, namely, labour productivity and superior technology that will tend to be more environmentally benign Labour productivity in the FO plant may, however, also be higher because more output-per-employee emerges due to the use of a superior technology The superior technology explanation can embrace more than simply a swifter rate of engineering or scientific advance in FO firms It may also incorporate “soft technology” aspects with superior managerial and production organisation practices (e.g Total Quality Control) Thus superior technology enables firms with the same level of capital-per-worker, to produce more output per unit-of-labour (position FO1 in Figure 1) The other extreme is that higher labour productivity may simply arise because a plant uses more capital-per-worker (position FO 2), so while labour productivity is higher, capital productivity is lower The evidence (at least for the UK) suggests that the superior technology explanation is likely to predominate (see Harris, 1999ab) Yet in the face of uniform environmental regulations across plants and a competitive market, variations in PAE should in large part be explained by differences in plant efficiency Contingent on their overall stringency, more efficient plants should require less PAE to satisfy any given environmental regulations However, in terms of the dynamics underlying the competitive process, efficient firms may also be the most likely to lead in the adoption of resource minimizing and hence cost-saving production techniques The latter view implies a greater tendency towards voluntary overcompliance (Arora and Gangopadhyay 1995) by efficient firms with respect to environmental regulations This effect has been observed in a developing country context For example, Eskeland and Harrison (1997) present evidence that foreign-owned plants in four developing countries were significantly less polluting than comparable domestic plants This overcompliance effect could be inferred from systematically greater PAE in efficient firms than in inefficient plants Overcompliance has been explained in terms of its possible role as an element in a non-price competitive strategy (Kirchhoff 2000) In this sense it can be exploited in some consumer markets as a source of competitive advantage on the grounds of quality differentials Indeed when such markets are also characterized by highly asymmetric information between firms and consumers, there also arises the potential for “greenwash” i.e where firms lie about their environmental performance (Kirchhoff 2000) However, in the context of intermediate goods markets such as metal manufacturing, this is a less convincing explanation for overcompliance More likely is an explanation based on a process of passive evolution linked principally to the notion of a sunk cost or path dependency argument Turning to Figure 2, it is likely that each technology choice will be associated with differing levels of resource productivity (Y/R) Resource productivity can be increased by recovering more of the potential residuals discharge from the production process to serve as output In general, Technology in Figure could offer greater resource productivity than Technology based on a number of processes including wholly in-plant recycling of raw materials, the use of generated heat from production as an energy source, and re-use of waste materials as another product line If a technology forcing environmental regulation was introduced to try to induce a higher level of resource productivity, then this could require a shift to a level of technology superior to Technology (Note, Figure also suggests that greater resource productivity is also associated in heavy industry with greater capital intensity.) In the context of the metal manufacturing industry over the relevant data time period, the prevailing regulatory instrument across all plants was indeed a technology-forcing standard determined by reference to an ambiguous and inefficient guiding doctrine – BATNEEC – Best Available Technology Not Entailing Excessive Cost This was formally introduced in UK statute within the 1990 Environmental Protection Act On this basis there was greater regulatory pressure to install a capital stock within newer plants that would be closer in function to the “best available technology” (BAT D) level in the domestic market However, under this guiding principle, environmental regulators could be minded to tolerate some level of departure from this BAT D standard in older established plants, where it might generate an excessive “corporate burden” (Pearce and Brisson 1993) By implication this involved the environmental regulators forming an implicit view as to an acceptable rate of return for the firm The older established domestic firm could thus meet the requirement for greater resource productivity whilst retaining most existing capital This could be undertaken by augmenting the existing capital stock with additional discrete pollution abatement orientated capital Alternatively, the firm could re-assign existing staff or hire new staff to engage exclusively in pollution abatement related tasks This would inevitably reduce labour productivity Whichever option or combination is applied, let this departure from the domestic level of BATD be represented by Technology S in Figure Accordingly, it is likely that FO firms have a systematic tendency to overcomply (Y/R FO2 > Y/RUK-owned) and ‘overspend’ on pollution abatement This can arise from a combination of (i) higher mainstream production capital intensity (K/L FO1 > K/LUK-owned) which will generally support greater residual recovery in heavy industry, or, (ii) because the transplanted production technology intrinsically embodies a given higher level of resource productivity This would accord with the notion that FO firms may have experience of stricter environmental regulation in their home country (say where BATDomestic < BATForeign) Hence, for this reason they are, at least in the short run, locked into an environmentally superior technology Even in the long run such firms would have to make a judgement concerning the extent to which they would meet expected future levels of stringency of environmental regulations and set that against any benefits from relaxing resource productivity (reducing overcompliance) Given that one would generally expect environmental regulations to be increasingly stringent over time, then overcompliance, especially by FO firms, seems likely to persist even in the long run Thus, the arguments presented here suggest that factors such as foreign-ownership, capitalintensity, efficiency, and the age of the plant are likely to be important in determining PAE More explicitly, distilled from the above discussion, premised largely on the overcompliance explanation, the main hypotheses that are tested in the subsequent econometric phase are: (i) FO plants engage in greater PAE than domestically owned firms (ii) More capital intensive plants engage in greater PAE (iii) More efficient firms engage in greater PAE (iv) Older plants engage in greater end-of-pipe (capital augmenting) PAE In addressing a uniform technology-forcing standard, PAE decisions can also reasonably be viewed as a sequential decision process First, firms decide whether they need to spend or not on pollution control They also need to decide what level and what type of pollution abatement expenditures they wish to make Given that certain types of pollution abatement expenditures are intrinsically more expensive than others, then it seems reasonable to suppose that the level and type of expenditure decision could be considered jointly To test whether different forms of pollution abatement expenditure are complements or substitutes to each other would require the estimation of a simultaneous model However, we not have the econometric tools to estimate a simultaneous Heckman model (see below for details), and furthermore we lack prior information that would allow us to impose some structure on such a model (i.e., which variables should enter which equation in the 2-stage Heckman approach in order to identify the system) Thus, as a first attempt we have resorted in the econometric phase to Another potential influence is the location of the plant - this is discussed in section when the model for estimation is presented estimating a reduced-form version of such a structural system Yet to inform such model development it is first necessary to broadly appreciate the significance and scale of the focus of this study – the UK metal manufacturing industry III UK Metal Manufacturing Industry 1991-4: Background Metal manufacture and use is vital to the social and economic prosperity of the entire globe, and most nations participate to some degree in its manufacture (Roberts 1996) In the UK the metal manufacturing industry comprises a presence in both iron and steel (ferrous metal) and non-ferrous metal manufacture Of the former, this includes manufacture of basic products such as steel tubes and steel wire as well as drawing, cold rolling and forming of steel to be used in the manufacture of other products In terms of non-ferrous metals this primarily comprises the manufacture of aluminium and aluminium alloys, copper, brass and other copper alloys There are also some plants manufacturing some other non-ferrous metals and their alloys The source, nature and method of assembly of the metal industry panel data available from the ARD used in this and the next section are described in the Appendix By way of critical assessment of the data it should be noted that it was collected as part of the UK government's Annual Business Inquiry that forms the basis of the 'official' statistics used to measure output and costs in each industry The government use a stratified sampling procedure to ensure that the data collected achieve good coverage of each industry, and since employment information is available for each plant (whether included in the annual inquiry or not) it is possible to weight the data to obtain nationally representative figures As such, the data we use is likely to be both accurate (in terms of point estimates of pollution expenditures) and contain sufficient coverage of the industry to make its use statistically robust when testing the types of hypotheses suggested in the previous section Metal manufacturing has long been a significant source of environmental pollution (Braennvall et al 1999) It poses considerable health risks to both workers (Comba et al 1992, De et al 1995, Maynard et al 1997, Moulin et al 1998), and the public (Baxter et al 1996, Guinee et al 1999) Its role in diminishing the quality of the physical environment has also been the subject of much scrutiny (Tremmel 1992, Dudka and Adriano 1997, Guinee et al 1999) In contrast with most other industrial sectors the waste residuals produced in metal manufacturing are largely non-dissipative (i.e not immediately or gradually dispersed into air, water or soil in the course of their normal use) (Kneese et al 1970) The residuals comprise bulky solids (e.g slag), much particulate matter, gaseous emissions from energy conversion, and much liquid waste resulting from cleaning or “pickling” the metal during fabrication to reduce oxide scales when the metal has contact with air The principal pickling agent for steel is sulphuric acid, but other acids such as hydrochloric, nitric and hydrofluoric are also used Slag may be re-used in road construction aggregates and in concrete manufacture A substantial volume of the particulates produced in the foundries as “flue dust” can be recovered “by wet scrubbing” and other precipitation processes due to their relatively high metal contents Other particulates such as soot from coke and coal burning (used in reheating furnaces and rolling mills) can also be captured by various forms of carbon filters and scrubbers Most of the liquid waste acids can be neutralized with lime but recovery has been considered problematic (Marquardt and Nagel 1992) That said, from the liquid wastes in most plants it has been possible to generate commercial grade ferrous chloride solution for use in flocculation processes in water treatment plants These processes also apply in some non-ferrous metal manufacture (copper and brass mills) but in addition with regard to copper, lead and zinc, some very concentrated and highly toxic sulphur dioxide fumes are also generated Some of this sulphur may now, however, be recovered as commercial grade sulphuric acid Thus, it can be seen that environmental pollution is a major ‘output’ of the metals industries Before considering PAE in this section and by way of context, it is instructive to look at the pattern of PAE across the UK manufacturing sector as a whole In this way any distinctive features of metal manufacturing can be drawn out As a consequence of the heavy pollution potential of this industry considered above, the declared expenditure per plant on managing waste residuals is relatively high, only exceeded on average by three other sectors (see Figure 3) In the manufacturing sector as a whole, of those plants that spend on pollution control, payments to others to manage and dispose of their waste dominates over this time period as the prime means of dealing with waste residuals (Figure 4) Recasting this picture in terms of plant ownership categories, UK manufacturing plants seem to lag behind in PAE with regard to all means of pollution control except payments to others (Figure 5) Turning now to the metal industry specifically (Figure 6), over the period 1991-4 average annual spending by plant on current staff for pollution control seems to have risen significantly from 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Economics and Statistics 41 255-67 20 Appendix The Data The UK metal industry panel data used is comprised of the individual records of the Annual Census of Production (ACOP) (now the Annual Business Inquiry) They are available from the UK Office for National Statistics (ONS) branch located in Newport, South Wales For each year there are two files that can be merged to produce plant level data One file covers the sample of establishments 9, known as the ‘selected’ file, who were asked questions about financial matters (e.g amounts spent on capital expenditure, including any pre-production expenditure) The other file contains information (such as employment and ownership structure) on ‘non-selected’ establishments (the remainder of the population) Establishment level data can be ‘spread back’ to plants using employment shares and the unique reference number allocated to each plant Using plant-level estimates of capital expenditure (on plant and machinery) based on acquisitions less disposals and including pre-production expenditure, it is possible to estimate the capital stock for each plant Further, it is possible to this using the same methods (and length-of-life assumptions) as those used by the ONS when they calculate the ‘official’ estimates for the UK Plant and machinery price deflators, supplied by the ONS were applied to the data, to produce real gross investment in plant and machinery by industry (see Harris and Drinkwater, 2000, for a discussion) Estimates of gross value-added, were converted to real prices using 4-digit indices of producer prices (inputs and outputs) provided by the ONS (i.e., we double-deflated using gross output and intermediate outputs to obtain real gross value-added) Regarding employment data, this was extracted from the individual records of the ACOP These estimates (together with the estimates for capital expenditure and output) were aggregated to the industry level and compared to the published estimates in the various annual reports of the ACOP Establishments are either single plants or they make a return that covers several plants –details and definitions are provided in the introductory notes for each annual census 21 Typically, the margin of difference between the two estimates for ALL manufacturing industry was in the region of 1% Where differences did occur, this is likely to be due to the fact that the individual returns database can have additional records added after the ACOP summary tables are compiled We used a more detailed procedure to obtain population weights (based on industries at the 4-digit level sub-divided into size bands where this was possible) and in addition some errors (such as duplicate cases) were discovered in the ACOP database 22 Table 1: Definitions of variables used and (weighted) mean and standard deviation values Variables Definition Mean S.D Proportion spending on: Assets used for post-production pollution Post-production capex 0.096 0.295 Process capex 0.080 0.271 0.132 0.338 0.244 0.429 Total Amount (log of £’000) spent on: Assets used for post-production pollution Post-production capex 0.326 0.469 1.283 2.233 Process capex 1.297 2.430 0.906 2.483 1.038 2.108 1.619 2.316 Frontier production function estimate of technical efficiency (see Harris, 1999b) Real gross-value-added in £m 1990 prices the age of the plant (i.e t minus year opened + 1, with all plants opening z-value (a) Post-production capital expenditure ln EFF 0.031 ln GVA 0.102 ln AGE -0.447 ln KL 0.303 ln DEN -0.090 − t EU 0.131 US 0.523 AUS 0.526 SIC 2220 0.498 SIC 2234 -0.076 SIC 2235 -0.576 SIC 2245 0.542 SIC 2246 0.998 SIC 2247 0.806 Constant 1.040 ρ − σ − λ − Log L pˆ -1061.355 0.132 0.39 3.77 -7.61 7.29 -3.01 − 0.77 3.67 3.30 3.48 -0.54 -2.15 4.16 6.14 5.82 3.36 − − − ∂pˆ x100 ∂x i 0.58 1.90 -8.28 5.62 -1.68 − 2.58 11.84 12.11 10.80 -1.37 -8.16 11.98 25.24 19.45 − − − − N Censored N z-value βˆ − 0.798 − − − -0.134 0.950 0.554 -0.305 0.474 0.118 1.373 0.804 0.733 1.202 2.334 -0.556 1.405 -0.781 − 19.68 − − − -1.64 2.63 1.66 -0.96 1.40 0.31 1.80 2.59 2.14 3.77 4.39 -2.88 3.58 -2.80 1912 1608 Cont… 24 (b) Process capital expenditure ln EFF 0.165 ln GVA 0.055 ln AGE -0.451 ln KL 0.363 ln DEN -0.149 − t EU 0.113 US -0.800 AUS 0.246 SIC 2220 0.139 SIC 2234 -0.722 SIC 2235 0.308 SIC 2245 -0.092 SIC 2246 0.236 SIC 2247 0.137 Constant 2.021 ρ − σ − λ − Log L pˆ -1044.655 0.132 1.89 1.94 -7.31 8.30 -4.59 − 0.67 -3.74 1.48 0.94 -4.60 1.84 -0.65 1.28 0.88 6.30 − − − N Censored N (c) Current expenditure on staff, etc ln EFF -0.277 ln GVA 0.110 ln AGE -0.282 ln KL 0.192 ln DEN -0.152 − t EU 0.200 US -0.632 AUS 0.885 SIC 2220 0.045 SIC 2234 -0.701 SIC 2235 -0.557 SIC 2245 0.051 SIC 2246 1.017 SIC 2247 0.549 Constant 0.934 ρ − σ − λ − Log L pˆ -1502.077 0.214 -4.19 4.31 -5.30 5.34 -5.38 − 1.33 -3.72 5.80 0.34 -5.41 -2.96 0.42 6.51 3.95 3.40 − − − n Censored N 3.07 1.03 -8.38 6.74 -2.77 − 2.20 -10.33 5.08 2.70 -10.67 6.40 -1.65 4.77 2.68 − − − − − 0.892 − − − -0.203 -0.196 -1.558 0.109 0.753 1.666 0.919 1.758 2.094 1.850 2.024 -0.505 1.330 -0.671 − 23.65 − − − -2.76 -0.55 -2.43 0.35 2.53 3.13 3.07 5.43 6.29 6.83 4.16 -1.92 2.67 -1.90 − 0.908 − − − -0.067 -0.773 -0.457 0.954 -0.909 1.018 0.586 0.394 -0.692 0.825 2.374 -0.553 1.374 -0.760 − 27.48 − − − 1.13 -2.90 -1.08 4.86 -3.65 2.84 1.26 1.78 -3.44 4.03 7.42 -3.02 4.05 -3.02 1912 1627 -6.84 2.72 -6.97 4.74 -3.77 − 5.24 -12.73 26.66 1.11 -15.25 -11.60 1.26 30.79 15.33 − − − − 1912 1430 Cont 25 ( d ) Payments to others ln EFF -0.147 ln GVA 0.104 ln AGE -0.195 ln KL 0.142 ln DEN -0.038 − t EU 0.371 US -1.125 AUS 0.420 SIC 2220 0.639 SIC 2234 -0.478 SIC 2235 0.060 SIC 2245 0.700 SIC 2246 0.639 SIC 2247 0.500 Constant 0.440 ρ − σ − λ − Log L pˆ -2198.781 0.375 -2.39 4.46 -4.18 4.49 -1.55 − 0.25 -6.08 2.83 5.20 -4.15 0.43 6.08 4.29 3.80 1.91 − − − N Censored N -4.77 3.40 -6.37 4.62 -1.23 − 1.21 -29.05 14.20 21.72 -15.67 1.99 24.17 21.63 16.92 − − − − − 0.967 − − − -0.157 1.058 -0.896 1.008 0.464 0.195 0.395 0.479 0.981 0.449 0.344 -0.624 1.289 -0.805 − 34.77 − − − -3.88 5.58 -2.26 5.14 2.67 0.91 1.85 2.77 5.17 2.49 1.44 -5.52 14.72 4.08 1912 1082 26 Figure 1; Technology Choice, Ownership and Productivity Figure 2: Ownership, Resource Productivity and Capital Intensity 27 Figure 3: Average (real) pollution control expenditure per plant*, 1991-1994, by industry: all manufacturing * includes only plants with positive expenditure Data weighted by population weights Note, the (population weighted) estimate of total spending in all industries was £738.1 million p.a for the 1991-94 period 28 Figure 4: Average (real) expenditure p.a on pollution expenditure control* (and percentage of plants with positive expenditure), 1991-1994: all manufacturing * includes only plants with positive expenditure Data weighted by population weights 29 Figure 5: Average (real) expenditure per plant*, 1991-1994, by type and ownership group: all manufacturing * includes only plants with positive expenditure Data weighted by population weights 30 Figure 6: Average (real) expenditure p.a on pollution expenditure control* (and percentage of plants with positive expenditure), 1991-1994: metal industry * includes only plants with positive expenditure Data weighted by population weights 31 Figure 7: Average (real) expenditure per plant*, 1991-1994, by type and ownership group: metal industry * includes only plants with positive expenditure Data weighted by population weights 32323232 32 ... that various plant level characteristics determine whether it is in the interests of the plant to actually spend anything on pollution abatement If the answer is 'yes' then the scale of output (and... expenditure) still seem remarkably small given the scale and nature of the production processes being undertaken The small magnitudes of these declared levels of PAE (in the context of this pollution. .. whether they need to spend or not on pollution control They also need to decide what level and what type of pollution abatement expenditures they wish to make Given that certain types of pollution