FIRM INNOVATION AND PRODUCTIVITY IN LATIN AMERICA AND THE CARIBBEAN - - PowerPoint PPT Presentation

FIRM INNOVATION AND PRODUCTIVITY IN LATIN AMERICA AND THE CARIBBEAN

The Engine of Economic Development

Carlo Pietrobelli

IDB - Competitiveness and Innovation Division carlop@iadb.org

www.firmsinlatinamerica.com MEIDE Conference, HSE, Moscow, June 16-17, 2016 OPEN ACCESS https://publications.iadb.org/handle/11319/7690

What is the problem? GDP pc growth is not fast

5000 10000 15000 20000 25000 30000 35000 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Latin America & Caribbean China Korea, Rep. East Asia & Pacific OECD members

Table 1: Growth Accounting: LAC vs Comparison Countries (1960-2011) (%) Country/ Region

D GDP per capita (a) D Factor Accumulation (b) D TFP (c) % Share (c) / (a)

LAC 1.79 1.80

• 0.01
• 0.6%

East Asia &Pac. 3.69 2.85 0.83 22.5% United States 1.99 1.21 0.78 39.2% China 6.04 4.21 1.83 30.3% Finland 2.74 1.44 1.30 47.4%

Why? Low Productivity Growth

Low Productivity Growth

TFP Relative to the US, 1960–2013 (in percent)

How can we explain this?

Focusing on aggregate data, we miss the effects of resource reallocation and within firms dynamics Two microeconomic sources of productivity growth drive aggregate efficiency over time:

1

Efficiency gains that occur within firms, due to better production methods, organization, innovation at the plant-level, learning and capability development, etc. Efficiency gains derived from the reallocation of resources from less productive firms to more productive

• nes - due to competition and

processes of (Schumpeterian) creation and destruction - entry (exit) of more (less) efficient firms.

2

Huge Heterogeneity among firms

in productivity and innovation (also within sectors)

Why we focus on 1

Grazzi & Pietrobelli, 2016, Busso et al., 2012 Hsieh and Klenow 2009 Syverson 2011

Labor Productivity Manufacturing Services

Many low productive firms Few highly productive firms

Huge Heterogeneity among firms

in productivity and innovation (also within sectors)

Why we focus on 1 – heterogeneity in productivity in LA

Data

• We use World Bank Enterprise Survey data to empirically analyze

the determinants of productivity at the firm level.

• Together with other databases such as EPFE (Productivity and

Human Resources Training Establishments Survey), TIVA, Foreign banks’ international presence, PROTEQIN (firm-level innovation datasets for 14 Caribbean countries)

• WBES: firm-level data on 135 countries, 2006, 2010, with

collaboration WB-IDB http://www.enterprisesurveys.org

• It covers 17 countries from Latin America and 14 countries from

the Caribbean from manufacturing and service sector

• ES in LAC includes questions on innovation, and access to policies

1. Determinants of Enterprise Performance in Latin America and the Caribbean: what does the micro- evidence tell us? Carlo Pietrobelli, Matteo Grazzi, Eddy Szirmai

• 2. Innovation Dynamics and Productivity: Evidence for Latin America

Gustavo Crespi, Fernando Vargas, Ezequiel Tacsir

• 3. Innovative Activity in the Caribbean: Drivers, Benefits, and Obstacles

Patrick K Watson, Eric Strobl, Preeya Mohan

• 4. ICT, Innovation and Productivity: Evidence from Latin American and the Caribbean Firms

Matteo Grazzi, Juan Jung

• 5. On-the-Job Training in Latin America and the Caribbean: Recent Evidence

David Rosas Shady, Carolina González Velosa, Roberto Flores Lima

• 6. Business Performance in Young Latin American Firms

Hugo Kantis, Juan Federico, Pablo Angelelli, Sabrina Ibarra Garcia

• 7. Different Obstacles for Different Productivity Levels? An Analysis of Caribbean Firms

Alison Cathles, Siobhan Pangerl

• 8. Credit Access in Latin American Enterprises

Roberta Rabellotti, Andrea F. Presbitero

• 9. International Linkages, Value Added Trade and LAC Firms' Productivity

Pierluigi Montalbano, Silvia Nenci, Carlo Pietrobelli

• 10. Innovation and Productivity in Latin America and the Caribbean Firms: Conclusions

Carlo Pietrobelli, Matteo Grazzi, Eddy Szirmai

RESULTS

Innovation improves productivity

• 1. First, LA firms are more likely to introduce product or

process innovation if they spend more on innovation. +10% in R&D spending = +1.7 percent increase in the probability to innovate and an increase of innovative sales of 1.3%.

• 2. Second, labor productivity of innovative firms in LA is on

average 50% higher than that of non-innovative firms.

• 3. These mechanisms vary largely depending on firm

capabilities and characteristics. e.g. size, product diversification and fixed investment, the quality of human capital.

1

Ln(Q/L) Ln(Q/L) Ln(Q/L) Ln(Q/L) (1) (2) (3) (4) Materials 0.5025*** 0.5028*** 0.5028*** 0.5070*** (0.0208) (0.0191) (0.0190) (0.0174) Capital 0.0919*** 0.0914*** 0.0918*** 0.0903*** (0.0075) (0.0078) (0.0089) (0.0080) Human capital 0.4821*** 0.4915*** 0.5170*** 0.4957*** (0.0557) (0.0548) (0.0556) (0.0637) Employment 0.0777*** 0.0783*** 0.0909*** 0.0766*** (0.0110) (0.0099) (0.0093) (0.0112) Manager experience −0.0003 −0.0005 −0.0007 −0.0004 (0.0007) (0.0006) (0.0006) (0.0007) Innovation 0.5543*** — — — (0.0879) Product innovation — 0.3635*** — — (0.1195) Process innovation — 0.1860 0.0636 — (0.1307) (0.1746) Innovative sales — — 0.5225** — (0.2113) IPRs — — — 0.3477*** (0.0865) N 4376 4376 4376 4376 Ll −3596.6234 −3596.8416 −3597.4046 −3607.396 chi2 14787.2106 9124.5645 13287.8438 17278.7706 P 0.0000 0.0000 0.0000 0.0000 Source: Authors’ elaboration using WBES.

Notes: Coefficients reported are marginal effects. Bootstrapped standard errors in parentheses.

Positive significant impacts of innovation on productivity

Caribbean firms: Are they special?

Spending on innovation has a higher return than in most LA. A unit increase in logged innovation expenditure per employee increases the probability of an innovation by 56%. Innovation improves productivity performance. Labor productivity of innovative firms is on average 63 percent higher than that of non-innovative firms.

.2 .4 .6 .8 1 1 2 3 4 Productivity Innovative Non-Innovative

The productivity benefits of innovation and human capital are greater for firms that are already productive

2

Broadband matters both for innovation and productivity, but only if is utilized well

Broadband adoption has a positive and significant effect on innovation (both in products and processes) and productivity

3

Use of Internet also affects probability to innovate, but…

• Only if used for Research
• the broader the variety of activities

for which broadband is used, the greater the impact on innovation

Broadband matters both for innovation and productivity, but only if is utilized well!

3

Variables

Product innovation Process innovation

(1) (2) (3) (4)

Broadband adoption 0.214*** 0.064 0.255*** 0.094** (0.036) (0.044) (0.039) (0.047) Internet use for purchases 0.016 0.019 (0.019) (0.020) Internet use to deliver services 0.013 0.038* (0.020) (0.020) Internet use for research 0.112*** 0.105*** (0.020) (0.021) Internet for purchases + deliver services + research 0.060** 0.048* (0.024) (0.025) Log Likelihood

• 4929,68 -4868,86
• 5017,95
• 4961,54

Rho

• 0.170** -0.145** -0.269*** -0.242***

(0.067) (0.067) (0.071) (0.072) /athrho

• 0.172** -0.146** -0.276*** -0.247***

(0.069) (0.069) (0.076) (0.077) Observations 5930 5930 5926 5926

Source: Grazzi and Jung (2016)

Firms decide to invest in training only if they also spend in R&D, innovate, have credit, face demand for (higher) skills

4

Has ISO certificate % Expenditure in R&D Improved processes Credit with financial institition Introduced new products Lack of skills is a major obstable Age of the firm Number of employees Number of competitors Fraction of domestic sales Fraction of temporary workers Experience of highest manager Fraction of skilled workers Fraction of domestic property

• .2

.2 .4

• .2

.2 .4

• .2

.2 .4

Small Medium Large

Marginal Effects

Training in firms has effect on productivity only for large firms

5

EFFECT OF TRAINING ON PRODUCTIVITY (1) (2) (3) (4)

Intensity

−0.001 −0.001 −0.001 −0.001 (0.001) (0.001) (0.001) (0.001)

Intensity * Large Firm

0.006* 0.007* n.a. n.a. (0.004) (0.004)

Intensity * Improved Processes

n.a. n.a.

• 0.003

0.002 (0.002) (0.002)

Observations

1479 1461 1479 1461

Firm-level fixed effects

Yes Yes Yes Yes

Time varying controls

No Yes No Yes

Source: Authorsʼ calculations based on WBES. Notes: This table presents estimates of the effect of increasing the proportion of trained workers. Standard errors are in

• parentheses. * Coefficient is statistically significant at the 10% level, ** at the 5% level, *** at the 1% level; no asterisk

means the coefficient is not different from zero with statistical significance. n.a. = not applicable.

Young firms tend to be less productive in the region

6

Neither the introduction of innovations nor the adoption of diversification strategies do seem to affect young firms’ productivity significantly

Productivity Gap between Young and Mature Firms (Median Values) Sector Productivity Gap in 2009 (Mature firms=100) Productivity Gap in 2007 (Mature firms=100) Manufacturing 79.4 73.7 Commerce 73.9 84.4 Services 81.1 70.3 Total 79.2 72.8

Source: Own elaboration based on Enterprise Survey

The productivity gap between young and mature firms is around 20%

7

Access to credit (in the Caribbean)

7

• In the Caribbean, among credit constrained firms

those that suffer most from poor access to credit for their productivity performance are both the most and the least productive

• The latter are trapped in a low productivity - low

credit access cycle, whilst the most productive ones appear to miss credit for innovation activities

8

Openness to international markets – via Exports, FDI, Global Value Chains – helps productivity

Positive productivity premia associated with the participation in trade and the presence of inward FDI The actual level of involvement into GVCs matters for the firms productivity in four big Latin American countries

(Argentina, Brazil, Chile and Mexico),

Moreover, being upstream in a GVC has a positive impact on firms’

• productivity. …. Firms operating in the industries exporting

intermediates and primary goods used in other countries’ exports

8

Participation and position in GVCs…..

8

Source: Adapted from Koopman et al. (2011)

Figure 1. Gross Export Decomposition in Value Added

GVC participation=IVA+FVA and GVC position=IVA/FVA

8

Trade in Value Added Components: IVA and FVA Higher productivity for firms upstream in GVCs (IVA>FVA)

8

What do we learn for public policies?

• Policies are needed that target within-firm

improvements (Crespi et al., 2014). So far macroeconomic reforms in LAC have not been sufficient to foster productivity and growth to satisfactory levels.

• Heterogeneity of firms requires policies tailored to

distinct firm needs. For example in innovation policies, specific policies for specific kinds of firms: Low productivity firms: Technology extension services, on-the-job training, etc. High Productivity firms: University industry collaborations, contract research, specialized labs, etc.

THANK YOU! OPEN ACCESS https://publications.iadb.org/handle/11319/7690 http://www.palgrave.com/us/book/9781349581504 www.firmsinlatinamerica.com

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CDM Model as baseline model