Background

Determinants of productivity in Morocco – the role of

trade?

Michael GasiorekPatricia AugierGonzalo Varela

Part of a DFID funded study entitled:

Analysis of the Effective Economic Impact of Tariff Dismantling

(under the Euro-Med Association Agreements)

Background• In the long run a key determining factor of GDP, and

growth of GDP, is productivity and productivity growth.• Well-established literature on relationship between

trade / openness & economic growth (eg.Winters, AER, 2004).– Most tend to accept that openness leads to higher growth

rates... but clearly the “environment” in which this occurs matters.

• Much smaller literature on what are the mechanisms driving (these) change in aggregate productivity?

• These changes in aggregate productivity will be driven by changes in productivity at the level of the firm

• More recently, work has started to use firm-level data sets in order to address such questions (Griliches & Regev, Tybout, Barnard, Levinsohn & Petrin….). – Aim of this work is to capture heterogeneity at the firm level

and to understand:• the sources of productivity growth across time• the sources of productivity differences across firms

• Possible sources of growth in total factor productivity:1. inter-industry reallocation of resources to more

productive sectors according to shifts in comparative advantage

2. Within industry compositional shifts• More productive firms increasing their share of the market• Entry and exit of firms

3. Existing firm becoming more productive:• efficiency gains from economies of scale (could be internal &

external, though the focus is typically on internal)• Technical progress (ie shifts in the production function);

– R&D, technological spillovers, improved quality of (imported intermediates)…

• Decrease in technical efficiency (ie reductions in the distance each firm is from its production frontier).

• Note the policy implications vary substantially depending on the extent to which changes in TFP are driven by each of the above.

Decomposing TFP growth

1. based on detailed firm level (FACS) survey of Moroccan industry for 1998 and 1999.

• extremely detailed based on seven sectors: clothing, textiles, food processing, chemicals, plastic, leather, electrical machinery.

• accounts for 53% of industrial production, 85% of exports, and 70% of manufacturing workers

• Advantage of the survey is that it is extremely detailed (eg. including information at the product level, direction of exports, information on imported intermediates etc)

• Disadvantage is that the data is only for two years, therefore some of the interesting questions regarding inter-sectoral and intra-sectoral compositional changes cannot really be addressed.

2. Time series data derived from the Annual Census of Manufacturing

• has the advantage of the time series dimension, therefore can perhaps better capture the impact of changes (in explanatory variables) over time.

• in principle also has data on more sectors than FACS• has the disadvantage of much less detail with regard to the

possible explanatory variables

Data: an overview

1. 1980’s saw beginnings of external trade reform, and this was taken further from the mid-1990’s onwards

• Morocco becoming a member of WTO and liberalising MFN tariffs

• Barcelona process and Association Agreement with the EU• bilateral FTAs

Morocco: policy overview

1993 1997 2000

Food 72 61 52

Textiles 92 61 38

Clothing 99 71 50

Leather 60 50 43

Chemical 47 35 26

R&P 61 48 38

Electrical 65 37 17

2. Other policy initiatives: privatisation, reform of labour law, exchange rate policy

• 2-stage methodology:– Estimate / calculate a measure of productivity at the

firm level• Parametric approach ie. econometrically estimate a

production function• Non-parametric aproach ie. using index numbers• (Data Envelopment Analysis)

– For the time series analysis:• examine the evolution of productivity over time• regress productivity on a shorter list of explanatory variables

(age, size, share of exports in output)

– For the FACS survery regress that measure of productivity on a list of possible explanatory variables...• Trade barrier, and intermedate input variables• R&D and capital variables• other firm specific variables (age, FDI, ISO certification,

industrial action, skill level of work force...)

Methodology

Aggregate productivity over time

2.5

2.6

2.7

2.8

2.9

3

3.1

3.2

3.3

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Year

TFP

TFP

Productivity by sector

1990199119921993199419951996199719981999200020012002

Year

Pro

du

ctiv

ity Food

Textiles

Clothing

Leather

Chemicals

Plastics

Electrical

Productivity and its determinants - time series

Sectoral FE

Firm level FE

Sectoral FE

Firm level FE First differences

expout1 0.016** 0.016** 0.138** 0.17** 0.0759*size2 0.494** 0.196** 0.503** 0.179**

size3 1.007** 0.252** 0.944** 0.137**

Size 0.068*age 0.007** 0.029** 0.006** 0.033**

sqage 0 0** 0 0** -0.598**skunsk1 0.023+ 0.003 0.078Expoutsec -0.195 -0.08 0.252Impoutsec -0.034 -0.143* -0.132*Constant 1.777** 1.582** 2.398** 1.548**

1990-2002 1996-2000

**, *, + denote significance at 1%, 5% and 10% levels respectively

...by sector and size

Small Medium Large

expout1 0.281** 0.1** 0.047expoutsec1 -0.859** 0.123 0.269impoutsec1 -1.055** -0.05 0.418*skunsk1 -0.103+ 0.003 -0.02age 0.034+ 0.049** 0.002Constant 1.62** 1.621** 2.29**

Food Textiles Clothing LeatherChemicals R & P Electrical

15 17 18 19 24 25 31

expout1 0.01** 0.02** 0.046** 0.093 0.041** 0.163+ 0.087+size2 0.294** 0.16** 0.141** 0.049 0.143** 0.164+ 0.047size3 0.221** 0.307** 0.136** 0.097 0.21* 0.028 0.235+Age 0.021** 0.036** 0.034** 0.012 0.076** 0.018* 0.023+Sqage 0** 0** 0** 0 -0.001** 0 0Constant 1.971** 1.391** 1.053** 1.546** 2.416** 1.149** 4.12**

1. Trade barrier variables: Tariff barriers on exports; Non-tariff barriers on exports; average domestic tariffs

2. Intermediate trade variables: Share of imported intermediates; Share of imported capital; Share of imported raw materials; Duty paid on imported capital

3. Other trade variables: Share of production exported (calculated at the firm level); Share of production exported (calculated at the sectoral level); Preparation undertaken for trade liberalisation with the EU.

4. R&D variables: Does the firm invest in R&D; No of products less than 5 years old; Share of workforce in R&D

5. Capital variables: Age of capital less then 5 years old; Age of capital between 5 & 10 years old; Age of capital more than 10 years old; Training by suppliers (of new machinery); Training undertaken abroad; Training from manuals

6. Other: Share of foreign ownership; Has the firm experienced any infrastructure related difficulties in the preceding year; Is the firm multiplant?; Has the firm applied for MEDA funding; Are the firm’s products ISO certified; No. of employees

Second Stage:

K-J Index

IV OLS

Tariff barrier variables

Tariff obstacles on Xs 0.173 - 0.127 - 0.114

NTBs obstacles on X’s

0.643***

0.484 0.490

Ave dom. tariffs - 0.296*

- 0.438***

- 0.398***

Intermediate trade variables

Share of imported interm.

- 0.032 0.056 0.033

Share of imported K - 0.207 - 0.059 - 0.062

Share of imported raw mat.

0.101 0.038 0.065

Duty paid on equipment

- 2.143 - 1.309* - 1.054

Other trade variables

Share of prod. exported

0.004**

0.001 0.001

Exp penetration (sector)

- 0.052 - 0.032 - 0.071

Preparation for trade w/EU

- 0.077 0.010 0.006

Productivity and its determinants? - trade

K-J Index

IV OLS

R&D variables - - -

Capital variables

Age of capital < 5 years

- 0.227 0.409**

0.387*

Age of capital: 5 < 10 years

0.248 0.460**

0.482**

Age of capital > 10 years

- 0.349 0.252 0.273

Infrastructure problems - 0.323**

- 0.072 - 0.086

Market share - 0.272 0.382**

0.429**

MEDA funding applied for?

0.394*

0.143 0.175**

Are the products ISO certified

0.531**

0.030 0.104

No of employees 0.083 - 0.029 0.009

Share. of foreign. own - 0.210 - 0.186* - 0.215**

Productivity and its determinants? - R&D and Capital

1. Different approaches to productivity yield highly comparable results; little evidence of returns to scale

2. Time series analysis indicates:• increase in productivity over time, though not in more

recent years• some evidence of positive correlation between

exporting and (increases in) productivity in aggregate• relationship between trade and productivity different

according to the size class of the firm and the industry being considered.

3. More productive firms tend to:• face lower domestic tariffs, • more obstacles in export markets for their products,

use newer capital, • have a larger domestic market share, • may have applied for MEDA funding, and • may have products which are ISO certifies

Summary

Note importance of the heterogeneity of firms:• little evidence that in aggregate firms are

becoming more productive• evidence suggests high levels of turnover of firms -

why? What are the constraints firms face?• exporting is associated with higher productity

levels - issues of causality and underlying mechanisms; potential role of deep integration

• why are exiting firms typically more producting than entrants - is this a product of the learning process, or are there structural impediments eg. access to credit

• similarly need to consider carefully the negative correlation between domestic openness and productivity - cold shower of competition v structural impediments

• role of informal sector

Policy Conclusions

Background

Documents

Transcript of Background