Filippo di Mauro CompNet Chairman, NUS-Business School Visiting Professor

1. Structural Changesin the Global EconomyCanberra, 21-22 August 2017 Productivity Puzzles Filippo DI MAURO Filippo di Mauro CompNet Chairman, NUS-Business School Visiting Professor (*) Skillfull research assistance from Bernardo Mottironi (Bocconi University) is gratefully acknowledged

2. Outline Productivity puzzles 1. The steady decline of productivity 2. Possible explanations 3. Some stylized facts using CompNetresearch 4. Conclusions

3. A first historical perspective Sources of USGDP Growth (% p.a.) • Post Great Depression to 1948 - Laborforce highest contribution • 1948-1973 golden era of growth - Productivity largest contributor - Labor force growth second highest • Sharp slowdown in 1970s, with negative productivity contribution (also extra-US)  oil price shocks/lower energy use  lower output per same K, N • Resurgence of growth since early 1980s, particularly from mid-1990s  ICT revolution (Higher investment/productivity) Edward Denison, BLS

4. Most recent Productivity devopmentsUS

5. Recent Productivity developments in the OECD

6. The productivity puzzle: Explanations • Will review the most common SIX standard explanations as outlined in Haldane (2017) • 1. The mis-measurement hypothesis • 2. Crisis-related scarring • 3. Slowing innovation • 4. Forbearance and monetary policy • 5. Diffusion dynamic • 6. Deteriorating resources reallocation • For the LAST TWO of them will get into some more detail, using in particular research results out of CompNet, the Productivity research network

7. The productivity puzzle: Explanations • The mis-measurement hypothesis: statistical mirage, failure to capture elements of the digitalrevolution. • Only a smaller share of the “utility” provided by new products (e.g. the smartphone) is embodied in their prices • Products’ price deflators were rising too fast (or falling too slowly) relative to their pre-2004 changes • But many of the mismeasurement problems already existedlong before productivity started slowing. • Syversen (2016) points out evidences against this hypothesis: • i) The magnitude of the slowdown in a country is unrelated to the relative size of ICTs in the country’s economy • ii) Even the largest result from literature on consumer surplus of new technologies (which accounts for the time people spend online with generous assumptions) totals only 1/3 of the missing output • => Much of the productivity slowdown is real

8. The productivity puzzle: Explanations • 2. Crisis-related scarring: the financial crises hada permanent/ persistent scarring effect on output. • via a collapse in credit availability constraining firms growth • …but ….as credit conditions have substantially eased, this is a less compelling explanation. • via a fall in property prices, whichhas tightened collateral constraints and credit conditions for firms. • …but ….as asset prices have recovered substantially, this is also not a convincing explanation.

9. The productivity puzzle: Explanations • 3. Slowing Innovation • The type of technological progress behind productivity growth over the past two centuries may not continue at the same pace in the future (Gordon, 2012) • the current wave of innovation, grounded in ICT, does not have the same potential as past innovations, and is also quite mature already, thus with low potential • As world population will peak this century, so will the pace of innovation. •  but…. there are many emerging – potentially revolutionary - technologies coming up, such as robotics, artificial intelligence, Big Data and the human genome

10. The productivity puzzle: Explanations • 4. Forbearance and monetary policy • productivity may have been held back by the actions of the authorities, in particular regulatory forbearance and accommodative monetary policies. • By supporting low-productivity companies (“zombies”), whichotherwise would have failed, policy actions may have prevented the “creative destruction” of firms. • This explanation may have some support….the level of company liquidations and firm exits (Business Churn) has remained low in many countries since the financial crisis, probably lower than would have been expected given the path of GDP.

11. Business churn (business birth + death rate) • While the difference of the two components (business birth & death) is an indicator of the number of firms growth, the sum of them (business churn)summarizes the share of replacement in the market • The declining trend (especially in the US) shows that the “creative destruction” is not working Source: Draghi (2017)

12. The CompNet research contribution Research network founded in 2012 to foster the debate on competitiveness/productivity It aims at providing a robust theoretical and empirical link between drivers of competitiveness/productivity and macroeconomic performance Partner Institutions: European Bank of Reconstruction and Development (EBRD); European Central Bank (ECB); European Commission (EC); European Investment Bank (EIB); Halle Institute for Economic Research (IWH); Tinbergen Institute (TI).  What is CompNet?

13. Built by some 20 EU based teams using their firm leveldata Indicators are aggregated to sectoral level (NACE 2-digit) in order to avoid confidentiality issues Unique in terms of its coverage and cross-dimensional analysis potential as it links, for example, trade or the financial status of firms with their productivity. Variables include employment, trade, productivity, mark-ups, financial constraints and more Definitions and computation are harmonized across countries We gather moments of the distributions for these variables. Joint distributions are also available. This allows you to analyze, for instance, whether more productive firms grow faster or whether firms with high mark-ups are less financially constrained The CompNet firm-level dataset

14. The productivity puzzle: Explanations • 5. Diffusion Dynamics • it arises, not from slower rates of innovation, but from slower rates of diffusion of innovation of the best performers to the rest of the economy • Possible explanations for such a phenomenon are: • Stifled competition in certain sectors which may have prevented the trickle-down of innovation, • management failings of small/less productive companies.

15. “Frontier” firms are diverging • Weakness in Aggregate productivity hides the fact that “frontier” firms remain highly productive • They are increasingly departing from “laggard” firms • Innovation diffusion is the key

16. “Frontier” firms are diverging …even more so for Services

17. Within sector firms heterogeneity is key ….within sector divergence is several fold higher than acrosssectors (Tradable and not)

18. The productivity puzzle: explanations • 6. Deteriorating resource reallocation • –Aggregate productivity is strongly related to the allocative efficiency of the factors of production (see next slide) • CompNet research has dealt with two main aspects • Determining the existence and the magnitude of a possible allocative inefficiency • Establishing possible causes for it • Conclusions • There is evidence of large Capital misallocation before the crisis and some “cleansing effect” during and after the crisis • In the long term, capital misallocation (as measured by HK index, see below) correlates strongly with demand uncertainty.

19. Allocative efficiency explains around 40% of TFP growth TOTALECONOMYSECTORSWITHINSECTORS Within-firm productivitygrowth: Firmincreasesitsown efficiency 50% Intra-sectorialTFP growth: Eachsectorgains productivity Allocativeefficiency: Available resources in the sector are allocated across firms to maximizeoutput 90% Aggregate TFP growth 50% Inter-sectorialTFP growth: Productivesectors gainweight 10%

20. Leastproductive Evidence 1 - Most productive firms are not credit constrained Share of credit costrainedfirms by deciles of labor productivity ICC index estimated within CompNet Mostproductive

21. The Hsieh-Klenow index Misallocation: inputs are not allocated efficiently across firms in a sector reallocating resources to the most productive firms would trigger growth • One of the mostpopular approach to measure misallocation has been proposed by Hsieh and Klenow(HK, 2009): Assumptions: • Without distortions the marginal revenue product of K and L are the same across all firms in a sector dispersion in MRP=0 • With distortions,reallocationofKtoLfromlowtohighproductivefirmsispreventeddispersioninMRP>0 • Hence,we measure misallocation of K, Las the within-sector dispersion of the MRPK, MRPL of firms operating in that sector  We useCompNetdata

22. Evidence 2 – Assessing misallocation via HK • Capital misallocation (proxied by MRPK dispersion) is trending up before the crisis and flat after; • Flatter overall trend for Labor Dispersion inMRPL Dispersion inMRPK Source: Gamberoni et al. (2016),calculations based on CompNetdata

23. Regression analysis on potential determinants • MRPI: Marginal product revenue of the input • Crisis (we have seen that crisis mattered): Dummy equal to 1 for years from 2009 onwards • Uncertainty (Firms’riskaversion;Bloometal,2014): Dispersion in the expectations of firms to future production • Real turnover (Controlforboomandboostin thebusinesscycle): Average growth in turnover across firms within sector • Credit constraint (Frictionsunrelated to firm productivity (Gilchrist et al., 2013)): Average interest rate on bank loans by country, sector • PMR: Product Market Regulation Index on legal barriers to entry • EPL: Employment Protection Legislation Index on strictness of labour regulation Source: Gamberoni et al. (2016)

24. Baseline results: MRPK dispersion Source: Gamberoni et al. (2016)

25. Demand uncertainty explains a large part of the MRPK dispersion Contribution of selected covariates to theexplanation ofchangesinMRPKdispersion (averagepercentagechanges) 25 Constant and fixedeffects Changes inPMR Changes in realturnover Residual 2002 MRPKdispersion Changes in demanduncertainty Crisisdummy Changes in cost ofcredit Changes in MRPKdispersion 20 4.5 4.7 4.4 15 3.5 3.2 1.9 1.2 2.6 1.4 0 1.1 1.1 0.3 0 0 0 1.1 1.1 0.1 1.1 0.5 1.1 0.3 1.1 1.1 1.1 0.8 10 13.0 12.4 12.1 13.0 12.5 12.1 12.5 12.1 12.1 5 0 0.5 0.3 --00..14 -00..52 -00..23 -0.3 -00..04 -0.6 -00..26 -0.7 --00..24 -1.1 -0.8 -1.2 -1.6 -1.8 -1.6 -1.6 -1.6 -0.6 -1.6 -5 -13.4 -13.4 -13.4 -13.4 -13.4 -13.4 -13.4 -13.4 -10 -13.4 -15 -20 2004 2005 2006 2007 2008 2009 2010 2011 2012 Source: Gamberoni et al. (2016)

26. The way ahead • The puzzle on lower productivity is still unresolved and is real, not just a result of accounting/mismeasurement. Is it necessarily going to stay with us? • From the evidence presented one could in principle take both extreme stands: •  Yes, we are doomed • - there is persistent capital misallocation • - innovation does not percolate properly across firms • - there is a low and decreasing business churning • - …. • No, productivity is bound to recover, even sharply • - New, revolutionary technology is about to come up • - Most productive firms are still thriving and stronger so • - post-crises normalisation can bring less uncertainty and higher investments in technology • - particularly in Europe, substantial structural reform will induce improved resource re-allocation •  I tend to lean with the latter camp

27. Sources • Bloom et al. (2014) “Really Uncertain Business Cycles”, Stanford University mimeo • Draghi, Mario (March 2017) –Fostering Innovation and Entrepreneurship in the Euro area • Gilchrist et al. (2015) – Misallocation and financial market frictions: some direct evidence from the dispersion in borrowing costs • Haldane, Andy (March 2017) - Speech on “Productivity puzzles” • Hsieh and Klenow (2009) – Misallocation and manufacturing TFP in China and India • Gamberoni et al (2016) - Capital and labour (mis)allocation in the euro-area • Gordon (2012) – Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds • P. Lopez-Garcia, F. di Mauro and the CompNet Task Force (2015) - Assessing European competitiveness: The new CompNet micro- based database, ECB WP Series, no.1764 • Syverson, Chad (2016) - Challenges to Mismeasurement Explanations for the U.S. Productivity Slowdown • Competitiveness Research Network –www.comp-net.org

28. Thanks for your attention

29. Reserve Slides

30. Motivation 1: Export growth by country

31. Motivation 2: Export levels aggregated

32. Motivation 3: Export levels by country

33. Motivation 4: Export levels by sector

34. These scatter plots reveal positive correlation between export and productivity at different levels of disaggregation Our specific focus is on 4: how firm level productivity affects sectoralexport performance across countries Traditional macro story: average(first moment) of firm productivity determines sectoral productivity and this in turn determines exports New micro story: higher moments of the productivity distribution matter too Present aim of paper

35. Producers have to be productive enough in order to export This means that a “fat right tail” of very productive firms matters above and beyond average firm productivity Selection effect: domestic firms suffer the competition of (the most productive) foreign exporting firms, which implies that only the most efficient domestic firms are able to survive in the market, leading to a reallocation of resources Recalling Melitz (2003)…

36. The rational of firm-level perspective • Firm performance distribution is very disperse and asymmetric • Rather than most firms around an “average” performance, there are lots of firms which have low productivity and only a few which are very productive in the “right-tail” of the distribution (the so called “happy few”) Evolution of labor productivity distribution in France Manufacturing sector - firms with 20+ employees Why do economists care about firm heterogeneity? Because they care that resources (capital and labour) are reallocated from low to high productive firms, in order to increase the economy aggregate performance 

37. 3 - What makes a firm a CHAMPION? Characteristics of firms from productivity point of view(a sample of some 8000 EU firms, EFIGE project) • Most productivefirms (i.e. theonesMovingorRemainabovethecut-off) tendtobe: • Larger (in termsofturnoverandnumberofemployees) • Have a larger capital stock per employee • Havelower Unit laborcosts......

38. 3 - The external dimension is critical Exporters Productivity Premium • Being an exporter is associated with higher levels of productivity (about 20%) • Export productivity premium is highly heterogeneous, it varies sharply across countries • During the crisis, the drop in productivity has been more pronounced for exporters

39. U.S. GDP since 1890 There was an enormous increase in U.S. output since 1890, by a factor of 46.

40. U.S. GDP per person since 1890 The increase in output is not simply the result of the large increase in U.S. population from 63 million to more than 300 million over this period. Output per person has risen by a factor of 9.

41. TFPgrowthisthemaindriverofGDPgrowth Trend and cross-country differences in GDP growth related to TFP growthdevelopments 2002-2007 2008-2014 Labourinput ICTcapital Non-ICTcapital Total factorproductivity GDPgrowth 6 5 4 3 2 1 0 -1 -2 Source: ConferenceBoard.

42. Potentialdeterminantsofmisallocationdynamics:1/2 • Product market regulation (PMR): Sheltering firms from competition might imply that low productive firms will keep operating instead of downsizing or exiting (Restuccia and Rogerson 2013; Andrews and Cingano 2014) • Labour market regulation (EPL): Stringent labour market regulation affect productive firms if they need to scale up or down quickly after a demand or technological shock (Haltiwanger, Scarpetta and Schweizer 2014; Bartelsman, Gautier and de Wind 2011) • Buttheycannotexplaintheoveralltrend…. ProductMarketRegulations-legalbarrierto entrysub-component Employment ProtectionLegislation Source: Authors‘ calculations based on OECD

43. 1. The mismeasurement hypothesis Has there been an effective productivity slowdown? • Some authors suggested this slowdown is substantially illusory, because the recent productivity gains are simply not reflected in the statistics. Why? Two potential reasons: • i) Only a smaller share of the “utility” provided by new products (e.g. the smartphone) is embodied in their prices, w.r.t. the share embodied by products introduced pre-2004: consumption of actual new products is very time-intensive but not particularly expensive (relative to the utility gains that they provide), so result in a modest impact on GDP • ii) Products’ price deflators were rising too fast (or falling too slowly) relative to their pre-2004 changes

44. Baseline results: MRPLdispersion

45. ThejointeffectofPMRandEPLreducedlabourmisallocation Contribution of selected covariates to the explanation ofchangesinMRPLdispersion Source: Gamberoni et al. (2016) 20