Productivity, Entry and Exit in Australian Manufacturing and Professional Services

Transcription

1 Productivity, Entry and Exit in Australian Manufacturing and Professional Services David Hansell and Thai Nguyen November 13, 2012 Abstract Competition promotes productivity growth as entrants compete with established firms and those with low productivity exit. In this paper we examine the performance of firms that enter and exit in manufacturing and professional services. Exiting firms not only have low productivity in the year prior to exit, but low productivity relative to established firms up to seven years prior. Entrants grow most rapidly in their second year of operation, but after five or more years are still below the level of established firms. At the division level, the main driver of productivity growth is continuing firms, and the net impact of firm turnover is negligible. However, this overlooks the cumulative impact of entry and exit over time. Over eight years, entry lowered growth by between three and eight per cent in manufacturing, and 12 per cent in professional services. In contrast, the exit of less productive firms raised productivity by between three and seven per cent in manufacturing, and 12 per cent in professional services. 1 Introduction Competitive markets foster the reallocation of inputs to more productive firms increasing aggregate productivity. The turnover of firms entering and exiting industries is part of this competitive process as entering firms vie for market share and exiting firms cease consuming inputs. Separating the contribution of continuing, entering and exiting firms to overall growth can be done various ways. Crucial to all methods are the benchmarks used to compare firms. Early firm-level studies show large gains from entry and exit, yet subsequent analysis and the development of different methods reveals these effects to be less pronounced. In this paper we use apply three decompositions that we argue accurately convey the impact of firm turnover to productivity growth. The first, developed by Baldwin and David Hansell and Thai Nguyen work for the Australian Bureau of Statistics (ABS), but the views expressed here are the personal views of the authors and do not represent the views of the ABS. The authors would like to thank Stephen Howe for methodological advice and Warren Cote, Calvin Ng and Rowan Hethey for their help and advice in accessing data. 1

2 Gu (2006) and Baldwin and Lafrance (2011), uses different productivity reference levels depending on which firms gain or lose market share. The other two, developed by Diewert and Fox (2010) and Melitz and Polanec (2012), use the productivity reference level of incumbents in the base and end years, but differ in their treatment of how productivity growth within and between continuing firms is measured. While the results from all three at times appear to contradict each other, they all provide different ways of interpreting the heterogenous nature of growth and decay among firms and industries over time. The data used in this study includes around half of all firms operating in manufacturing, and certain classes of professional services over the period to Our results show that entering and exiting firms in these industries have lower productivity than continuing firms. The productivity of entering firms increases most in their second year of operation. Exiting firms exhibit low productivity years prior to exit a pattern evident prior to the rising terms of trade. Entrants lower aggregate productivity in their year of entry as they establish market share, while exiting firms raise productivity by ceasing to operate. The net impact of entry and exit at the division level is neglible when compared to the growth of continuing firms. However, among the constituent industries net entry can be important a fact disguised by the higher level of aggregation. Section two describes the methodology. Readers not interested in technical detail can skip to section three, which describes the data used and provides some descriptive statistics on entering and exiting firms. Section four presents the results of the decompositions and the impact of entering and exiting firms to aggregate growth. Section five concludes. 2 Methodology Most methods of decomposing productivity start by defining aggregate productivity P t as the weighted sum of all firms i that operate within the market at time t. 1 That is, aggregate productivity is defined to be, P t = i s it p it. where s it and p it are firm shares and productivity. The change in productivity for the group is (P t P t 1 )/P t 1 if measured in levels or (P t P t 1 ) if measured in logs. In this paper, we use employment shares and value-added per full-time equivalent (FTE) employees as our productivity measure. 2 1 Another strand advocates using a Bennet productivity-change indicator as the preferred measure of productivity change, see Fox (2012) and Breunig and Wong (2008). 2 For ease of exposition, we present the decompositions in logs. However we implement them in levels by dividing through base-period productivity as the log approximation is inexact, particularly when dealing with small firms that exhibit large percentage changes in productivity. 2

3 2.1 Decomposing Productivity Growth A popular study by Baily, Hulten and Campbell (1992) spurred numerous studies on the role of firm turnover to productivity growth. A symmetric version of their decomposition into the contribution of continuing, entering and exiting firms is, P t = s it p it + s it p it + s it p it i C t,t 1 i C t,t 1 i N t i X t 1 s i,t 1 p i,t 1 (1) where the bar above a terms indicates the two-period average of the firm, and is the change over the base and end year. The first term is the change in productivity within firms, while the second is the change between firms. Alternatively these can be thought of as the changes in productivity due to technical progress and the reallocation of inputs among firms respectively. The third term is the contribution of entering firms and the last term subtracts the contribution of exiting firms. One problem with this decomposition is that entering firms always increase productivity and exiting firms always decrease it. This is because it ignores the different productivity levels among continuing, entering and exiting firms. A solution is to introduce a reference level as a benchmark. 3 In a series of papers Baldwin and Gu (2006) and Baldwin and Lafrance (2011) (henceforth BGL) argue the benchmark should be determined by which firms gain or lose market share. 4 If entering firms displace exiting firms, then the productivity change should be decomposed by, P t = s it p it + s it (p it P X )+ s it (p it P X ) i C t,t 1 i C t,t 1 i N t i X t 1 s i,t 1 (p i,t 1 P X ) (2) where P X is the share-weighted base-year productivity of exiting firms and is given by, P X = s i,t 1 p i,t 1 1 s i,t 1 i X t 1 i X t 1 Note that by definition the final term is zero and only the net effect of entry and exit is measurable (via the third term in (2)). If entrants gain market share from incumbents, BGL propose the base-year productivity of continuing firms that lose market share, denoted by P D, as the reference level. This leads to the decomposition, P t = i C t,t 1 s it p it + i C t,t 1 s it (p it P D ) + i X t 1 s i,t 1 (P N p i,t 1 ) + (S N S X )(P N P D ) 3 The choice of what reference level of productivity is selected influences the measured contribution of the three groups of firms. This can lead to different policy conclusions and so is not an innocuous decision. See appendix for a more thorough discussion. 4 This line of argument can be found in earlier works of Baldwin (1995) and Caves (1998). (3) 3

4 where S N and S X are the total shares of entering and exiting firms, and P N is the weighted productivity of entrants in the end period. Finally if the share of entrants is less than exiting firms and a subset of continuing firms gain market share at the expense of exiters or other incumbent firms, then productivity should be decomposed as, P t = s it p it + s it (p it P G ) + s it (p it P X ) + (S X S N )(P G P X ) (4) i C t,t 1 i C t,t 1 i N t where P G is the base-year productivity of continuing firms that increased their share over the two years. In contrast, Diewert and Fox (2010) and Melitz and Polanec (2012) use two reference levels: continuing firms in the base (P C1 ) and end years (P C2 ). This allows the productivity of entering and exiting firms to be measured against the industry productivity level from the year in which they operated. The first stage of separating the contribution of continuing, entering and exiting firms is, P t = (P C2 P C1 ) + S N (P N P C2 ) + S X (P C1 P X ) (5) Diewert and Fox (DF) then define a within and between term for continuing firms using the shares for continuing firms, denoted by sc, 5 i C t,t 1 sc it p it + i C t,t 1 sc it p it (6) Melitz and Polanec (MP) adapt a method proposed by Olley-Pakes (1996) that decomposes productivity into the unweighted average productivity and a covariance-type term to reflect the interaction of market share and productivity. The former measures the change in the productivity distribution via its first moment and the latter reflects the interaction of shares and productivity. The contribution of continuing firms is, 1 p it 1 n n i C t i C t 1 p i,t 1 + (sc it sc t)(p it p t ) (sc i,t 1 sc t 1)(p i,t 1 p t 1 ) (7) i Ct i C t 1 As with DF, MP use the shares of continuing firms in the covariance term. 6 When discussing the decomposition results, we label the change in the unweighted mean as the within-firm effect, and the change in the covariance term as the between-firm effect. However, it is important to remember they provide different information on the contribution of continuing firms. The within-firm and between-firm effects in BGL and 5 Note the shares of continuing firms sc sum to one in each period. 6 MP also show that the entry and exit terms can be further decomposed into covariance terms, which we do not calculate here to simplify the comparison with BGL. In levels all components of BGL and DF and the entry and exit terms from MP are divided through P t 1. However, the within and between term effects of MP are divided through (1 cov S)P t 1, where cov S = 1/2( cov S2 + cov S1), and cov S = i C t (sc it sc t)(p it p t ). 4

5 DF are weighted by employment shares whereas the MP within term is the change of the unweighted mean of continuing firms. Thus when the two differ it indicates firms of different size are growing at different rates. 3 Data The data set used covers the period to Firm-level measures of valueadded and employment are drawn from a combination of two data sets: Business Activity Statements (BAS) and Business Income Tax (BIT). 7 This data is merged with information from the ABS Business Register to obtain industry classifications and exclude firms with complex accounting structures. 8 ABS price indices are used to deflate value-added to prices. 9 Due to restrictions on the level of detailed price indices and the need to combine ANZSIC93 and ANZSIC06 industrial classifications, we restrict our analysis to the industries in table 1. Table 1: Industries in Scope Division Manufacturing Professional, Scientific and Technical Services ANZSIC93 Classification All except: Cigarette and Tobacco Product Bread and Cake Retailing (ANZSIC ) Scientific Research Architectural Surveying Consulting Engineering Computer Consultancy Accounting 3.1 Descriptive Statistics Table 2 contains the average annual number of observations in the sample (column 2), the number of observations as a proportion of total firms operating in the industry (column 3), and the average proportion of firms that enter (column 4) and exit the 7 These data are provided to the ABS for statistical purposes by the Australian Taxation Office (ATO). See appendix for a more detailed description of the data. 8 Firms with complex accounting structures are typically large businesses that operate across different industries and do not lodge all relevant information under one unique identifier. Consequently including these firms will lead to inaccurate estimates of a firm s productivity. Individuals reporting business income are also excluded but they only account for less than 1 per cent of total income in manufacturing and 9 per cent in professional services in See appendix for a more thorough discussion of how we derive full-time equivalent employees and the deflators used. 5

6 sample (column 5). 10 It shows that the sample encompasses around 40 to 60 per cent of firms in each industry and that the average rate of entry and exit is around nine per cent in manufacturing and 10 to 11 per cent in professional services. Table 2: Sample Characteristics Industry N Industry Entry Exit Total (%) (%) (%) Manufacturing 50, Food and Beverage 4, Textile, Clothing, Footwear, Leather 4, Wood and Paper Product 3, Printing, Publishing and Recorded Media 4, Petroleum, Coal, Chemical and Associated Product 3, Non-Metallic Mineral Product 2, Metal Product 10, Machinery and Equipment 10, Other Manufacturing 6, Professional, Scientific and Technical Services 60, Scientific Research 1, Architectural Services 7, Surveying Services 1, Consulting Engineering Services 16, Computer Consultancy Services 22, Accounting Services 11, All results are averages over to Industry totals are for Results for professional services are for the classes analysed, not the entire division. Table 3 contains averages of revenue (column 2), intermediate inputs (column 3), value-added per full-time equivalent (column 4), and full-time equivalent employees (column 5). Value-added per FTE is similar in both divisions, but manufacturing firms have higher turnover and intermediate inputs. The firms in our sample are relatively small, which is a consequence of excluding firms with complex accounting structures. Yet it is this characteristic we wish to exploit as small firms have high rates of entry and exit. 10 Total firms operating are from and from ABS cat no , Counts of Australian Businesses, including Entries and Exits. 6

7 Table 3: Summary Statistics Industry Revenue Int. VA FTE Inputs per FTE Manufacturing , Food and Beverage , Textile, Clothing, Footwear and Leather , Wood and Paper Product , Printing, Publishing and Recorded Media , Petroleum, Coal, Chemical and Associated Product , Non-Metallic Mineral Product , Metal Product , Machinery and Equipment , Other Manufacturing , Professional, Scientific and Technical , Scientific Research , Architectural Services , Surveying Services , Consulting Engineering Services , Computer Consultancy Services , Accounting Services , Note: All results are averages of deflated values over to As we decompose aggregate productivity, it is instructive to compare ABS estimates of gross value-added (columns 2 and 3), labour input (columns 4 and 5) and labour productivity (columns 6 and 7) with the sample estimates. Table 4 shows that the growth in value-added for the sample exceeds the industry as a whole, while the growth in hours worked is much closer to our estimate of FTEs. Consequently our estimates of the growth in labour productivity exceed ABS industry estimates, particularly for professional services. The differences are in part due to the exclusion of large businesses, and certain classes of services due to the difficulty of concording ANZSIC93 and ANZSIC06 classifications. Further our estimates for the growth among the classes in professional services vary substantially, and so excluding certain classes should lead to a difference with the industry aggregate. In addition, one should bear in mind that national accounting data is subject to historical revisions, which can affect annual movements. 7

8 Table 4: Comparison of ABS and Sample Totals: Value-added, Labour Inputs and Productivity Value-Added Labour Input Labour Productivity ABS 5204 Sample ABS 5204 Sample ABS 5204 Sample Manufacturing Professional, Scientific and Technical Services ABS cat no is the Australian System of National Accounts Next we consider the productivity of entering and exiting firms relative to continuing firms. Table 5 shows the difference in labour productivity weighted by employment shares where continuing firms take a value of 100. At the division level, exiting firms in manufacturing are 16.5 per cent below and entering firms 30 per cent below continuing firms, while in professional services they are 26 and 27 per cent less productive respectively. At finer levels of classification, there is considerable variation: entering firms in food and beverage manufacturing and exiting firms in scientific research are half as productive as continuing firms, while exiting firms in some industries are only around 10 per cent below continuing firms. In eight of the nine manufacturing subdivisions entrants are below exiting firms, which may reflect that most businesses take more than a year to build their sales while they incur material and labour costs. Alternatively it may reflect entering firms discounting relative to continuing firms and so revenue-based measures of productivity understate the physical productivity of entrants (Foster et al 2005). 8

9 Table 5: Relative Labour Productivity by Industry Industry Exit Entry Manufacturing Food and Beverage Textile, Clothing, Footwear and Leather Wood and Paper Product Printing, Publishing and Recorded Media Petroleum, Coal, Chemical and Associated Product Non-Metallic Mineral Product Metal Product Machinery and Equipment Other Manufacturing Professional, Scientific and Technical Scientific Research Architectural Services Surveying Services Consulting Engineering Services Computer Consultancy Services Accounting Services That entrants have lower productivity in their first year of operation says nothing about how these firms progress over time. To assess this, we compare the employmentweighted productivity of entrants that survived for a minimum of three years by cohort and compare them with firms that operated continuously. Table 6 contains the results for five entering cohorts. For example, column 2 gives the results for the cohort. The final column contains the mean of all cohorts post entry and does not correspond to the financial year in the first column it is the average of each cohort in its year of entry and subsequent years where the final value is for the cohort in Across all cohorts the pattern is similar: entering firms that survive experience their highest growth in their second year of operation. Entering firms in manufacturing go from 70 to 80 per cent as productive as established firms, and professional services firms from 75 to 88. Further entrants in manufacturing grow less rapidly relative to established firms. After four years of operation entrants are 10 per cent below, whereas those in professional services are only four per cent below established firms. 9

10 Table 6: Relative Labour Productivity Trajectory Post Entry by Industry Entry Cohort Mean Post-Entry Manufacturing Professional, Scientific and Technical Services A common finding in firm-level studies is that firms with low productivity have a higher likelihood of exit (Foster et al 2001). To evaluate whether this is the case we perform a similar exercise as with entrants and track cohorts of exiting firms prior to their year of exit. Table 7 shows the results for five cohorts of exiting firms relative to the same cohort of established firms Note that the mean pre-exit does not correspond to the financial year in column one. It is the average of all exiting cohorts where the final value is the average of all exiting cohorts in the year prior to exit, while the first is the value of firms that exited in

11 Table 7: Relative Labour Productivity Trajectory Pre-Exit by Industry Exit Cohort Mean Pre Exit Manufacturing Professional, Scientific and Technical Services Firms that exit in both industries have productivity levels around 20 to 30 per cent below established firms in their year prior to exit. Yet it is also clear that among all cohorts these firms are well below the level of established firms years prior to exit. The average of all cohorts three years prior to exit is around 15 per cent below the level of established firms. It is noteworthy that before the rise in Australia s terms of trade in around 2004, all exiting cohorts are below those of firms that survived over the entire period. Indeed, the cohort that exits in is eight per cent below the productivity level of established firms in Aside from the relative productivity differences with incumbents, the impact of new entrants on productivity growth depends on how many entering firms become established. Table 8 contains the proportion of entering firms by cohort that become incumbents post entry. What is striking is the degree of similarity in two quite different industries: around 87 per cent survive for two years, 75 per cent for three years and the cohort in both industries never differs by more than 1 per cent over seven years. Finally, these survival probabilities are quite similar to other OECD countries, such as the US and France, despite the time periods differing by a decade or more (OECD 2001). 11

12 Table 8: Proportion of Entrants that Survive Entry Cohort Years of Operation Mean Manufacturing Professional, Scientific and Technical Services If we compare the proportion of firms in the cohort that survived to their third year of operation with the average of the other cohorts, there is a clear difference: the proportion of firms that survived is 5.2 per cent lower in manufacturing, and 5.7 per cent lower in professional services. Establishing a causal link is beyond the scope of this paper, but it seems reasonable to infer that this difference is attributable to below trend economic growth, and changed lending conditions for SMEs. 12 The importance of entering and exiting firms to aggregate productivity is determined by their relative importance to the markets in which they operate. Table 9 contains average employment shares for the divisions and their constituent industries. 13 Among all manufacturing subdivisions, the average share of exiting firms is higher than entrants. At the division level in professional services, the shares of entering and exiting firms are approximately equal, but this conceals the different replacement processes among the consistuent classifications. 12 The RBA (2010) submission to the parliamentary committee on access for small and medium business to finance remarks that since the onset of the financial crisis in SMEs faced tighter lending conditions, increased spreads, and an easing of competition among lenders. 13 The shares don t sum to unity as the incumbent shares are the mean over each period; rather, the average of entering and exiting shares plus incumbents equals one. 12

13 Table 9: Average Employment Shares by Industry Industry Incumbents Entry Exit Manufacturing Food and Beverage Textile, Clothing, Footwear and Leather Wood and Paper Product Printing, Publishing and Recorded Media Petroleum, Coal, Chemical and Associated Non-Metallic Mineral Product Metal Product Machinery and Equipment Other Manufacturing Professional, Scientific and Technical Services Scientific Research Architectural Services Surveying Services Consulting Engineering Services Computer Consultancy Services Accounting Services Decomposing Labour Productivity We now consider the contribution of continuing, entering and exiting firms to overall productivity growth using the three decompositions in section 2. The results are presented relative to where the components of each method sum to the overall change. For example, the final row in table 10 for the components of each method adds up to the overall increase of per cent. All methods agree the dominant source of labour productivity growth in manufacturing is from within firms: the within-firm term for MP (24.23) exceeds the aggregate growth of 19 per cent, while DF (18.83) and BGL (17.79) are just below the overall change. 14 While the individual contributions of entry and exit are important, the net effect is small. Entering firms reduce productivity growth by either eight per cent (MP and DF) or three percent (BGL), while exiting firms raise productivity through ceasing operation by between seven per cent (MP and DF) or three per cent (BGL). The higher contribution of entry and exit in DF/MP is attributable to the different reference productivity levels used. 14 This finding is consistent with previous Australian studies (Bland & Will 2001; Parham 2002; and Nguyen 2009). 13

14 Table 10: Productivity Change Relative to Manufacturing Year Within Between Entry Exit Index MP DF BGL MP DF BGL MP/DF BGL MP/DF BGL The results also show an interesting contrast for the between effect. Viewing the MP result in isolation, one concludes market share reallocations subtract from aggregate growth. On the other hand, if one were to only apply DF and BGL, the opposite is true. The problem is both are correct. In DF the within term is weighted by employment shares, but MP in levels only accounts for shares via the covariance term. The difference of the two reflects the variation in productivity change among firms of different sizes. Continuing firms in manufacturing with between 6 and 15 FTEs, which account for around 20 per cent of employment shares, experience slower growth than smaller and larger firms. Table 11: Productivity Change Relative to Professional Services Year Within Between Entry Exit Net Entry Index MP DF BGL MP DF BGL DF/MP DF/MP BGL At the division level, the shares of entering and exiting firms are almost identical, and so we apply equation (2) and only show net entry for BGL in table 11. Similar to the results for manufacturing, if the contribution of entering firms is added to that for exiting the net result for both methods is close to zero. However, the DF and MP results show that over time entering firms lower aggregate growth by 12.6 per cent, and exiting firms increase growth by per cent. Thus while BGL is conceptually valid, it doesn t show whether entering firms are lowering or raising productivity. The within and between terms for DF and BGL differ from MP, but now the within terms for DF and BGL are and while for MP it is The difference is due to smaller continuing firms growing while the productivity of large firms is relatively stagnant. 14

15 Most firm-level studies note the heterogeneity of productivity among firms and industries. This is readily apparent when examining the finer industrial classifications. Table 12 contains the cumulative change of the decompositions by manufacturing subdivision relative to While the entry and exit contributions have the same sign, the net contribution is positive for all except food and beverage manufacturing. The greatest contribution of net entry is for textile, clothing, footwear and leather (9.65 and for DF/MP and BGL respectively) and is largely due to the exit of unproductive firms. Table 12: Cumulative Productivity Change Relative to Manufacturing Subdivision Subdivision Within Between Entry Exit MP DF BGL MP DF BGL DF/MP BGL DF/MP BGL The cumulative changes by finer classification in professional services are contained in table 13. As with manufacturing, the net impact of entry and exit differs significantly over time among the constituent classes. While the division level results show a neglible impact on growth, in scientific research (7810), surveying (7822) and accounting services (7842) the contribution of net entry is important. 16 Half of the aggregate growth in scientific research and three quarters in surveying is due to entry and exit. In accounting services, net entry lowers aggregate growth by -4.5 (DF/MP) or -3.9 (BGL) per cent, while aggregate growth is only 1.3 per cent over eight years. Table 13: Cumulative Productivity Change Relative to Professional Services Class Class Within Between Entry Exit MP DF BGL MP DF BGL DF/MP BGL DF/MP BGL Year by year changes are provided in the appendix and 7822 only account for an average of two and five per cent of the total employment for the division, and so their contribution to the division results is small. 15

16 5 Conclusion In this paper, we demonstrated that entering and exiting firms in manufacturing and professional services have lower productivity than established firms. Entrants experience their largest increase in productivity in the second year of operation and continue to improve over time. By tracking cohorts of exiting firms from , we find that these firms have lower productivity than established firms years prior to exit, which is at odds with the perception that Australia s terms of trade is largely to blame for firm closure in manufacturing. The proportion of entrants that survive over time is similar in our sample to that found in other major studies. However, the survival rate for firms that entered in is more than five per cent lower in than other entering cohorts in their third year of operation, which we infer is due to below trend growth and changed lending conditions since the onset of the financial crisis. The contribution of entry and exit to aggregate growth depends on which decomposition method is applied. In this paper, we applied three methods that use different reference levels to measure the contribution of continuing, entering and exiting firms. When analysing all firms in the same division, the net impact of entry and exit is neglible, but this disguises the cumulative impact of these effects over time. Entering firms lower aggregate productivity growth by between three and eight per cent in manufacturing, and around 12 per cent in professional services. Exiting firms raised aggregate productivity by three and six per cent in manufacturing, and 12 per cent in professional services. However at finer levels of industry classification, the results vary considerably and reinforce the notion that industries as well as firms have heterogenous productivity. References [1] Baily, Martin & Charles Hulten & David Campbell (1992) Productivity Dynamics in Manufacturing Plants Brookings Papers on Economic Activity, Microeconomics: [2] Baldwin, John, R. (1995) The Dynamics of Industrial Competition. New York: Cambridge University Press. [3] Baldwin, John, R. & Wulong Gu (2006) Plant Turnover and Productivity Growth in Canadian Manufacturing, Industrial and Corporate Change, 15(3): [4] Baldwin, John R. & Amelie Lafrance (2011) Firm Turnover and Productivity Growth in Selected Canadian Services Industries, 2000 to 2007, Statistics Canada cat no 11F0027M, Ottawa, Ontario. Economic Analysis Research Paper Series no 72. [5] Bland, Steven & Will, Lou (2001), Resource Movements and Labour Productivity, an Australian Illustration: to , Productivity Commission Staff Research Paper, AusInfo, Canberra. 16

17 [6] Breunig, Robert & Marnn-Heong Wong (2008) A Richer Understanding of Australia s Productivity Performance in the 1990s: Improved Estimates Based upon Firm-Level Panel Data, Economic Record Vol 84 (265): [7] Caves, Richard E. (1998) Industrial Organization and New Findings on the Turnover and Mobility of Firms, Journal of Economic Literature 36: [8] Diewert, W. Erwin & Kevin J. Fox (2010) On Measuring the Contribution of Entering and Exiting Firms to Aggregate Productivity Growth in W. Erwin Diewert, Bert M. Balk, Dennis Fixler, Kevin J. Fox and Alice O. Nakamura (eds) Price and Productivity Measurement: Volume 6 Index Number Theory Trafford Publishing, Victoria, Canada. [9] Foster, Lucia & John Haltiwanger & C.J. Krizan (2001), Aggregate Productivity Growth: Lessons from Microeconomic Evidence, in Hulten, C., Dean, E. and Harper, M., New Developments in Productivity Analysis, NBER Studies in Income and Wealth, vol. 63. [10] Foster, Lucia & John Haltiwanger & Chad Syverson (2005) Reallocation, Firm Turnover and Efficiency: Selection on Productivity or Profitability? NBER Working Paper No [11] Fox, Kevin J. (2012), Problems with (Dis)Aggregating Productivity, and Another Productivity Paradox, Journal of Productivity Analysis, 37: [12] Griliches, Zvi & Haim Regev (1995) Firm Productivity in Israeli Industry: , Journal of Econometrics, vol 65: [13] Melitz Marc J. & Saso Polanec (2012) Dynamic Olley-Pakes Productivity Decomposition with Entry and Exit NBER Working Paper No [14] Olley, Steven & Ariel Pakes (1996) The Dynamics of Productivity in the Telecommunications Equipment Industry Econometrica, Vol 64(6): [15] OECD (2001) Productivity and Firm Dynamics: Evidence from Microdata in OECD Economic Outlook No. 69 available at [16] Parham, D. (2002), The Role of Exit and Entry in Australian Productivity Growth, OECD Science, Technology and Industry Working Papers, 2002/06, OECD Publishing. [17] Nguyen, Thai V. (2009) Returns to Scale, Technical Progress and Firm Dynamics in Australia, Unpublished PhD Thesis University of New South Wales. [18] Reserve Bank of Australia (2010) Submission to the Inquiry into Access of Small Business to Finance 17

18 Appendix Deflators and Industry Classification All price deflators used are set to a base period of using price indexes from Producer Price Indexes, Australia (ABS cat no ). Although results in the paper are presented in terms of ANZSIC93 classifications, ABS stopped publishing producer price indexes for ANZSIC93 in All units were assigned ANZSIC06 and ANZSIC93 codes derived from the ABS Business Register. Firms that entered after ABS stopped updating ANZSIC93 classifications in the Business Register were assigned an appropriate ANZSIC93 code. 17 Construction of Full Time Equivalent Employee Estimates To derive an estimate of the number of employees we use unpublished survey data from the ABS Survey of Average Weekly Earnings to derive the average weekly wage for all persons at a three digit level for manufacturing and four digit level for professional services. Following this the wage bill is divided by the annualised average wage bill to calculate full time employee equivalents. Given the data set contains owner operators with no wage data, a value of one was imputed where wage data was unavailable. While in many cases a missing value is genuine, it is acknowledged that this can underestimate the true number of employees. Consequently, we exclude firms that have one or more values in the top or bottom 0.5 per cent of the productivity distribution over the period analysed. Productivity Decompositions and Reference Productivity Levels Prior to discussing reference levels, we review the decomposition of aggregate productivity. We start by letting F t denote the set of firms in year t, and noting that firms can exit or enter, and so F t F t 1. For each t and each firm i F t, we let p it and s it denote productivity and industry share respectively. Then we write the productivity of the industry as P t = i F t s it p it. Thus, industry productivity is the weighted average of the firm productivities using industry shares as weights. Further we let C denote continuing firms, which operate in the base and end-years, N denote entrants that operate in the end year, and X denote exiting firms that operate only in the base year. Now we can write the change in industry productivity as P t = s itp it s i,t 1p i,t 1 i F t i F t 1 = (s itp it s i,t 1p i,t 1) + s itp it s i,t 1p i,t 1 i C t,t 1 i N t i X t 1 = (s it p it + s itp it ) + s itp it s i,t 1p i,t 1 i C t,t 1 i N t i X t 1 = s it p it + s itp it + s itp it s i,t 1p i,t 1 i C t,t 1 i C t,t 1 i N t i X t 1 17 Note ANZSIC06 class 1174 (Non-Factory based Bakery Product Manufacturing) is excluded as it is in Retail Trade under ANZSIC93. 18

19 where the first and second terms of the last line are the change in productivity within and between continuing firms respectively, while the third and fourth terms are the contributions of entering and exiting firms. Thus we have a symmetric version of the Bailey, Hulten and Campbell (1992) decomposition. Unfortunately this is unsatisfactory as entering (exiting) firms always raise (lower) productivity irrespective of their productivity level. It is now useful to define a productivity reference level based on a subset of firms, P R,t = ( i R s it p it) ( i R s it ) 1 Also note that the sum of all shares in each period is equal to one, s it + s it s i,t 1 = (S Ct + S Nt ) (S C,t 1 + S X,t 1) i C t i N t i X t 1 = 1 1 = 0. Thus for any P R, which we call the productivity reference level, we have P t = s it p it + s itp it + s itp it s i,t 1p i,t 1 i C t i C t i N t i X t 1 P R s it + s it s i,t 1 i C t,1 1 i N t i X t 1 = i C t s it p it + i C t s it(p it P R) + i N t s it(p it P R). i X t 1 s i,t 1(p i,t 1 P R) Again we have a decomposition into four components, but now the between firm effect will only be positive if there is reallocation to firms that have productivity higher than the reference productivity, entering firms will make a positive contribution only if their share-weighted average productivity is higher than the reference productivity, and exiting firms will make a positive contribution only if their share-weighted average productivity is lower than the reference productivity. Now imagine a scenario in which the subset of continuing firms (P C ), experience an increase in productivity from t = 0 to t = 1, while entering (P N1 ) and exiting firms (P X0 ) are below the level of continuing firms in both periods. Figure 1 illustrates this point visually. 19

20 Figure 1: Productivity Reference Levels Table 14: Productivity Reference Levels for Entry and Exit Decomposition method Turnover contribution Griliches & Regev (GR) S N1(P N1 P ) + S X0( P P X0) Foster, Haltiwanger & Krizan (FHK) S N1(P N1 P 0) + S X0(P 0 P X0) Baldwin & Gu (1) S N1(P N1 P X0) + S X0(P X0 P X0) Baldwin & Gu (2) S N1(P N1 P D0) + S X0(P D0 P X0) Baldwin, & Lafrance (3) S N1(P N1 P X0)+(S X0 S N1)(P G0 P X0) Diewert-Fox & Melitz-Polanec (DF/MP) S N1(P N1 P C1) + S X0(P C0 P X0) Note: Reference levels are underlined Table 14 summarises the most common reference levels used in empirical studies. In the scenario depicted in figure 1, GR and FHK would show a positive contribution for entrants as P N1 is above the average and base-year productivity. In contrast DF/MP estimate entry to be negative as P N1 is below P C1. While GR, FHK, and DF/MP all show a positive contribution for exiting firms, GR is greater than DF/MP, which is greater than FHK. Given that the aggregate change is necessarily the same for all methods, when the net contribution of entrants and exiting firms is higher in one method, then the contribution of continuing firms will be lower than in the other method. The approach of BGL explicitly accounts for the replacement process. Thus if entrants have a similar market share as exiting firms, then entrants displace exiting firms and one only observes the difference of P N1 and P X0 ; but if entrants have a higher market share than exiting firms, then entrants displace exiting firms and incumbents in decline P D0 ; and, finally 20

21 if entrants have a lower market share than exiting firms, then growing incumbents P G0 are driving productivity and the contribution of entry and exit should be measured relative to this subset of firms. The contribution of entrants in Baldwin and Gu (1), and Baldwin and Lafrance (3) is the same, yet in the former the contribution of exit is zero and only net entry is measured. In practice the share of entrants will rarely, if ever, be exactly equal and it is at the discretion of the analyst as to which method is more appropriate. Nevertheless these methods explicitly take industry dynamics into account by measuring firms relative to those which they replace and are equally valid if one is satisfied with the underlying assumptions. 21

22 Table 15: Productivity Change Relative to Manufacturing Subdivision Year Within Between Entry Exit Index MP DF BGL MP DF BGL DF/MP BGL DF/MP BGL 21 - Food and Beverage Textile, Clothing, Footwear and Leather Wood and Paper Product Printing, Publishing and Recorded Media Petroleum, Coal, Chemical and Associated Continued on next page 22

23 Table 15 continued from previous page Year Within Between Entry Exit Index MP DF BGL MP DF BGL DF/MP BGL DF/MP BGL Index 26 - Non-Metallic Mineral Product Metal Product Machinery and Equipment Other Manufacturing