Investigating New Zealand-Australia Productivity Differences: New Comparisons at Industry Level

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Investigating New Zealand-Australia Productivity Differences: New Comparisons at Industry Level Productivity Hub Symposium: Unpicking New Zealand s Productivity Paradox Te Papa, Wellington, 2 July 2013 Geoff Mason National Institute of Economic and Social Research, London

Industry-level productivity comparisons: background NZ-Australia productivity differences have been widely analysed at aggregate economy level Less research on NZ s comparative strengths and weaknesses at industry level (except for IMF, 2002, and NZIER, 2011) Biggest difficulty has been lack of purchasing power parity (PPP) exchange rate estimates at industry level IMF (2002) used broad industry-level expenditure PPPs produced by OECD which are principally designed to assist with international comparisons of living standards NZIER (2011) used market exchange rates disadvantages of short-term volatility; plus limited relevance to nontraded goods

Key features of this study Use industry-specific PPP exchange rate estimates prepared by the Groningen Growth and Development Centre as well as latest OECD PPPs New estimates of capital-intensity and skills at industry level in NZ and Australia Underlying data based on most recent ANZSIC 2006 industrial classification in both countries available back to 1997 Benchmark comparisons of Average Labour Productivity (ALP) and relative Multi-Factor Productivity (MFP) levels in 24 market industries in 2009 New comparisons of ALP and MFP growth rates at industry level between 1997-2010

Order of presentation NZ-Australia productivity gap in long-term perspective Comparisons of ALP levels in market industries Relative capital-intensity and skill levels in both countries Comparisons of MFP levels in market industries Growth accounting: decomposition of ALP gaps between capital-intensity, skills and MFP components Identify proximate causes of NZ-Australia productivity differences at industry level Hope to clear the ground for new research into ultimate causes of these productivity differences

1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 Average labour productivity level (US=100) Figure 2.2: Average GDP per hour worked in New Zealand and Australia, 1956-2011, Index numbers: US=100 100 90 80 70 60 50 AUS NZ Source: Conference Board Total Economy Database, January 2012

1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 Indices of output and total hours worked (1967=100) Figure 2.3: Total GDP and annual hours worked in New Zealand and Australia, 1956-2011, Index numbers: 1967=100 450 400 350 300 250 200 AUS-Output NZ-Output AUS-Hours Worked NZ-Hours Worked 150 100 50 Source: Conference Board Total Economy Database, January 2012

PPP exchange rates Groningen PPP estimates for 1997 in US$ updated to 2009, using industry-level price deflators for the United States as well as for NZ and Australia Alternative industry-level PPP estimates derived from disaggregated PPP data obtained from OECD OECD price data more up to date than GGDC but gaps in product coverage by the OECD mean that industry-specific OECD PPP estimates can only be obtained for 11 of the 24 industries For the remaining industries, we use OECD PPPs derived for either GDP as a whole or for aggregated manufacturing or service industries All OECD-based PPP estimates adjusted for retail and wholesale trade and transportation margins and for taxes with the aid of industry-level information derived from Supply-Use Tables for each country

Comparisons of ALP levels, 2009 Using Groningen PPPs, estimated ALP in total market industries in NZ is 62% of the Australian level Using OECD PPPs, equivalent figure is 67% Using both sets of PPPs, Australia is ahead on ALP in agriculture, forestry and fishing; mining; most branches of manufacturing; construction; wholesale; retail; accommodation and food services; and financial services NZ is ahead on ALP in food and drink manufacturing; electricity, gas and water; rental, hiring and real estate services; and arts and recreation services Using Groningen PPPs alone, there are signs of NZ being ahead in professional, scientific and technical services and matching Australia in information media and telecoms services while Australia leads in transport, postal and warehousing

Differences in industrial structure (1) Shift-share decomposition: roughly 30% of the NZ- Australian gap in ALP for aggregate market industries can be attributed to differences in employment structure Australian employment more concentrated in industries with comparatively high absolute levels of value added per employee such as mining, utilities (electricity, gas and water) and financial services NZ employment more concentrated in comparatively low value added industries such as agriculture and manufacturing as a whole

Differences in industrial structure (2) Mean of NZ and Australian productivity levels (US$ per hour worked) NZ industry shares of total hours worked (%) Australian industry shares of total hours worked (%) Sector name Agriculture, forestry and fishing 17 10 5 Mining 151 1 3 Manufacturing 25 17 13 Electricity, gas, water and waste services 243 1 2 Construction 55 12 13 Knowledge-intensive services 55 18 20 Other services 25 42 44 TOTAL MARKET INDUSTRIES 40 100 100

Measuring relative capital-intensity (1) Derive benchmark comparisons of net capital stocks per hour worked at industry level in 2009 Start with National Accounts data on gross fixed capital formation for 1986-2009 Convert investment data to US$ using OECD PPPs for investment goods by asset type Use perpetual inventory method to cumulate constant price investments and deduct value of depreciated assets, using common industry-specific depreciation rates (US estimates) Then take 2009 benchmark comparison of net capital stocks per hour worked and use SNZ and ABS estimates of growth in capital services at industry level to generate 1997-2010 time series around the 2009 benchmark

Measuring relative capital-intensity (2) Biggest problems for comparability: SNZ estimates of intangible assets exclude R&D SNZ estimates of cultivated biological resources exclude livestock SNZ includes computers with other plant, machinery and equipment Distinguish four groups of capital assets which can be adequately compared between the two countries: Structures (comprising non-residential buildings and other construction) and land improvement (excluding livestock) Plant, machinery and equipment (including computers) Transport equipment Intangible assets (excluding R&D) Impact of excluded capital assets on relative ALP will be picked up in estimates of residual MFP

Relative levels of capital-intensity Across total market industries, average capital per hour worked in NZ is 62% of the Australian level Structures and land improvement 57% Plant, machinery and equipment (incl. computers) 78% Transport equipment 83% Intangible assets (excl. R&D) 78% Broadly consistent with previous findings using different methods (Hall and Scobie, 2005; Schreyer, 2006; NZIER, 2011) Australia ahead on capital-intensity in wide range of industries: agriculture, mining, manufacturing, construction, most services New Zealand more capital-intensive in only 5 of 24 industries and only one of these (electricity, gas and water) has a high absolute level of capital-intensity

Figure 4.1: Average capital per hour worked (US$2009), total market industries, 1997-2010

Explaining differences in relative capital-intensity Almost 40% of the Australian lead on average capital per hour worked can be attributed to differences in industrial structure Competing explanations regarding relatively low levels of business investment in NZ: Relatively low labour costs in NZ compared to the costs of capital (IMF, 2002; Hall and Scobie, 2005) Relatively high costs of borrowing for investment purposes in NZ, partly linked to relatively low rates of domestic saving (OECD, 2011) Negative effects of relatively low MFP levels on firms investment intentions (Dupuy and Beard, 2008) Hulten (2009) emphasises two-way interdependence between MFP and capital-deepening

Measuring relative skill levels Identify three qualification groups at industry level in each country: Graduates (Bachelor degrees and higher degrees) Post-secondary school qualifications below Bachelor degree level No post-school qualifications Benchmark on relatively low-skilled No post-school qualifications category and then use ratios of mean wages in the other two qualification groups to low-skilled wages in each country as indicators of labour quality differences between the respective qualification groups In this way all hours worked by workers in Groups 1 and 2 can be calculated as effective units of labour relative to Group 3

Australia-NZ differences in workforce qualifications Figure 5.1: Highest qualifications held by workers in total market industries, 1997-2010 Sources: Derived from ABS, Survey of Education and Work and SNZ, New Zealand Income Survey.

Pay differentials by qualification group Figure 5.2: Average pay ratios, 1997-2010, analysed by qualifications group Sources: Derived from ABS, Survey of Income and Housing and SNZ, New Zealand Income Survey.

Estimates of relative skill levels Figure 5.3: Trends in estimated skills index in total market industries, 1997-2010

Estimated skill differences at industry level Australian has narrow lead over New Zealand in total market industries of about three percentage points in 2009 Australia s narrow lead on measured skills in 2009 prevails in all individual market industries Gap only exceeds five percentage points in five industries: mining, chemicals, professional and scientific services, information media and telecommunications and finance and insurance

Estimating relative MFP levels In standard growth accounting approach, based on the neoclassical growth model, cross-country differences in average labour productivity (ALP) levels can be decomposed into three components reflecting differences in: Capital-intensity Labour quality (skills) Multi-factor productivity (MFP) MFP is estimated residually as the proportion of the crosscountry gap in ALP levels which cannot be explained by measured differences in capital-intensity and skills Thus MFP can be seen in large part as an indicator of the efficiency with which capital and labour inputs are utilised

Interpretation of MFP measure Among other things cross-country differences in estimated MFP levels may reflect differences in: capacity utilisation effectiveness with which new technologies are used implementation of innovative work practices diffusion of new ideas and knowledge between firms and industries speed of reallocation of resources from less efficient to more efficient firms firm sizes (production scale) impact of economies of agglomeration (through urban scale) At the same time, MFP measures also pick up the effects of unmeasured capital inputs such as land and investments in R&D and innovation which were not included in our capital stocks measure

Figure 6.1: Relative ALP and MFP levels in total market industries, 1997-2010 (Index numbers: Australia = 100)

Figure 6.2: Estimated contributions of relative capital-intensity, skills and MFP to the relative ALP gap in total market industries, 1997-2010

Industry differences in relative ALP and MFP levels Estimates suggest that Australia was ahead in 2009 on both ALP and MFP in 12 industries, including agriculture, mining, printing, transport equipment and machinery, construction, wholesale and retail, transport, postal and warehousing and financial services NZ ahead on both ALP and MFP in 5 industries: food and drink manufacturing, electricity, gas and water, rental, hiring and real estate services, professional/scientific services and arts and recreation services In 3 industries NZ ahead on MFP but behind on ALP: textiles and clothing manufacturing, wood and paper products and accommodation and food services Where a country is doing better on MFP than on ALP, the implication is that it benefits from advantages in some of the unmeasured or poorly measured variables which are captured in estimates of residual MFP

Estimated contributions to gap in ALP (proportions) AUSTRALIAN LEAD ON ALP Using Groningen PPP exchange rates ALP levels, 2009 (AUS =100) MFP levels, 2009 (AUS =100) Relative capitalintensity Relative skills Relative MFP TOTAL MARKET INDUSTRIES 62 78 0.39 0.03 0.58 Manufacturing 77 98 0.83 0.07 0.1 Printing 23 24 0.01 0.01 0.99 Financial and insurance services 30 48 0.23 0.02 0.75 Construction 36 35-0.02 0.01 1.01 Mining 43 47 0.05 0.01 0.94 Non-Metallic Mineral Product Manufacturing 46 56 0.17 0.01 0.82 Transport Equipment, Machinery and Equipment Mfg 48 62 0.25 0.02 0.73 Metal Product Manufacturing 49 96 0.89 0.02 0.10 Wholesale trade 52 77 0.49 0.02 0.48 Transport, postal and warehousing 57 71 0.28 0.03 0.68 Agriculture, forestry and fishing 62 86 0.63 0.01 0.36 Retail trade 62 72 0.23 0.03 0.74 Petroleum, Chemical, Polymer and Rubber Product Mf 67 94 0.74 0.06 0.20 Wood and Paper Products Manufacturing 77 105 1.16 0.05-0.21 Accommodation and food services 88 115 1.17 0.01-0.18 Textile, Leather, Clothing and Footwear Manufacturing 89 110 1.74 0.19-0.93

Estimated contributions to gap in ALP (proportions) NEW ZEALAND LEAD ON ALP Using Groningen PPP exchange rates ALP levels, 2009 (AUS =100) MFP levels, 2009 (AUS =100) Relative capitalintensity Relative skills Relative MFP Arts and recreation services 108 127-0.55-0.04 1.59 Food, Beverage and Tobacco Product Manufacturing 112 123-0.73-0.21 1.94 Other services 115 100 1.03-0.01-0.03 Furniture and Other Manufacturing 134 91 1.28-0.05-0.23 Professional, scientific and technical services 170 178 0.01-0.12 1.11 Electricity, gas, water and waste services 179 149 0.39-0.02 0.63 Rental, hiring and real estate services 247 255-0.04-0.01 1.06

Inter-industry variation in relative importance of capital-intensity and MFP (1) Focussing on 15 industries in which Australia was ahead on ALP in 2009: in six of them higher levels of capital-intensity are found to play a predominant role - metal product manufacturing, agriculture, forestry and fishing, chemicals and related industries, wood and paper products manufacturing, accommodation and food services and textiles and clothing manufacturing In another 8 industries it is MFP which contributes most to the Australian lead on ALP: printing, financial services, construction, mining, non-metallic mineral manufacturing, transport equipment and machinery, transport, postal and warehousing and retail trade In wholesale trade the contributions of MFP and capitalintensity to the Australian lead on ALP are roughly equal

Inter-industry variation in relative importance of capital-intensity and MFP (2) In 5 of 7 industries where New Zealand is ahead on ALP, the main contribution to that lead comes from MFP: rental, hiring and real estate services, electricity, gas and water, professional/scientific services, food and drink manufacturing and arts and recreation services Impact of relative capital-intensity exceeds that of MFP in miscellaneous manufacturing and other services but, in these industry groupings, absolute levels of capital-intensity are low in both countries Only one sector where New Zealand is ahead on ALP and relative capital-intensity is important is electricity, gas and water where capital accounts for just under 40% of New Zealand s ALP lead, still only two thirds of the MFP contribution

Figure 6.3: Annual growth rates in MFP in total market industries, 1997-2010

Recent trends in MFP growth at industry level Signs of NZ catch-up in MFP growth between 2004-08 but largely due to events in Australia In eight industries MFP in Australia during this period declined by an average -4% pa or even more: mining, food and drink manufacturing, chemicals and related industries, miscellaneous manufacturing, electricity, gas and water, financial and insurance services and rental, hiring and real estate services Much of this decline reflected unrequited growth in production inputs in Australia in response to transitory factors such as drought and more favourable terms of trade facing Australian producers (Parham, 2012) This period of adjustment may now be over: when recession hit in 2008-09, New Zealand was much more strongly affected than Australia in a range of industries

Assessment (1) Both relative MFP and relative capital-intensity contribute substantially to Australia s lead on ALP MFP predominates at total market industries level but there is wide variation between industries in the relative importance of MFP and capital-intensity Key questions for policy-makers: What are the main factors restricting MFP growth in NZ? What are the main factors which explain relatively low levels of business investment in all forms of capital human capital and innovation capital as well as physical capital? What, if anything, can government do in a cost-effective way to influence current levels of MFP performance and capital formation within NZ firms?

Assessment (2) New research at industry and firm level needed to gather information on causes of inter-country differences in: Proportion of firms operating at international technology frontier Diffusion of new ideas and knowledge across international borders and within New Zealand Speed of reallocation of resources between less efficient and more efficient firms in domestic product markets Vocational education and training element in different qualification groups Business investment in different forms of capital: skills, R&D and innovation capital as well as physical capital

SYMPOSIUM: UNPICKING NEW ZEALAND S PRODUCTIVITY PARADOX 2 July 2013, Oceania, Te Papa Tongarewa