On the 3rd of July 2018, Dr Chuah Lay Lian from the Macroeconomics and Growth team of the World Bank’s Development Research Group hub in Kuala Lumpur presented on the topic of “Resource Misallocation and Productivity Gaps in Malaysia”.

1. Resource Misallocation and Productivity
Gaps in Malaysia
Lay Lian Chuah, Norman V.Loayza and Ha Nguyen
June 7, 2018

2. Motivation
• Overarching question for development: Why are some countries’ productivity
high and some others’ low?
• A traditional candidate is technology.
- Policy implications include investing in innovation, FDI (technological
spillover), human capital etc
• New way of thinking:
- Resource misallocation1 (Restuccia and Rogerson (2008) , Hsieh and
Klenow (2009)). Policy implications are very different.
• Are markets generally good at allocating resources?
- Yes, within a distorted environment
Misallocation1
1See Banerjee and Duflo (2005) and Restuccia and Rogerson (2008)

3. Sources of Growth – A Review
Misallocation2
• Capital
• Labour
Increasing inputs
• Allocational (resources used in most
productive activities)
• Technical (more output from same inputs)
Increase efficiency
• New technologies
• Innovation
Increasing
productivity

4. Decomposing Sources of Growth
Misallocation3
Production Frontier 2
Production Frontier 1
Y
X
X1 X2
Y1
Y2
E2
E1
Increase in
technology
Y2-Y1 = Growth in output
E1 - E2=Growth from increasing efficiency
Z = Growth from increasing inputs from X1 to X2
T2-T1=Growth from technological change
Z
T1
Y1*
Y2*
T2
Y1’
Increase in inputs
Y2-Y1=E1-E2+Z+T2-T1

5. Growth Accounting Decomposition and Total Factor Productivity
(TFP)
Growth Accounting
Y=Akα(hL)1-α
where Y is GDP
A is total factor productivity (TFP)
K is physical capital stock
α is the output elasticity of physical capital
L is labour (number of workers)
h is the average level of human capital
Total Factor Productivity (TFP)
• TFP is the portion of output not explained by the amount of inputs used in production
• Differences are due to differences in technology or efficiency.
Misallocation4
Firm Workers + Machines = Output
Firm A 10 5 25
Firm B 10 5 35

6. Resource Misallocation – Distortions in Capital Market
Misallocation5
R* R*
Firm 1: Low Productivity Firm 2: High Productivity
Marginalrevenueproduct/
rentalrateofcapital
capital capital
R1
K1*
MRP
K2*
R2
K2
mK1
m
capital
capital
MRP
MRP
Marginalrevenueproduct/
rentalrateofcapital
Marginalrevenueproduct/
rentalrateofcapital
Marginalrevenueproduct/
rentalrateofcapital
𝝅 𝟏
𝝅 𝟐
𝝅 𝟏
𝒎
𝝅 𝟐
𝒎

7. Optimal Resource Allocation: Equalising Marginal Revenue Product
• An efficient economy is one where most firms in the same narrow industry have
the same marginal revenue product:
MRP1 = MRP2 = MRP
• An economy that's inefficient will be characterised by a large variance or kind of
wide distribution of marginal revenue products in the same industry
MRP1 ≠ MRP2 ≠ MRP
• Large potential gains to be made from reallocating resources more efficiently
Misallocation6

8. Misallocation Inferred from Distributions of “Revenue Productivity”
Misallocation7
• Wider dispersions for India
and China compared to the
US. This suggest:
• Larger variances in “revenue
productivity” for India and
China.
- Less efficient allocation
of resources.
- Larger distortions in
Indian and Chinese
economies.
More firms in the
left hand tail
More firms in
the left hand
tail
Source: Hsieh & Klenow (2009)
Distortions in allocation show up in the
variance of “revenue productivity”
across firms
𝑵𝒐𝒕𝒆: 𝑇𝐹𝑃𝑅 𝑠𝑖 ∝ (𝑀𝑅𝑃𝐾𝑠𝑖) 𝛼𝑠
(𝑀𝑃𝑅𝐿 𝑠𝑖)1−𝛼𝑠

9. Why Do We Observe Misallocation?
Why do some firms have more inputs than other firms – even when they have the
same technology?
Firms will hire labour and use capital until MPL = w and MRK = r. If that does not
happen (causing resource misallocation), it is possible that firms face different
prices.
How is that so?
• Government policies  subsidies; taxes on inputs or outputs based on certain
characteristics.
o Discretionary government provisions eg. subsidized access to land or capital
for some firms; tax breaks or low interest rate loans
o Unfair bidding practices for government contracts, preferential treatment
(“crony capitalism”)
• Firm characteristics
o Location of firms which adds more to cost
o Firm size:
- Differential access to finance and labor market
- Differential pricing power
Misallocation8

10. Resource Misallocation and Productivity Gaps in Malaysia
(i) Empirical Framework - Hsieh & Klenow (2009)
• Main assumptions
• Empirical model – key equations
(ii) Data
• Description of firms in the census data
(iii) Results
• The degree of misallocation in Malaysian manufacturing sector
• Comparison of misallocation across selected countries
(iv) Policy Implications & Conclusion

11. Questions
• How important is misallocation as a source of productivity differences in
Malaysia? What is the extent of Malaysia’s productivity gaps compare to its
peers? Which sectors experienced the biggest distortions?
• If there is misallocation, what are the potential sources causing misallocation?
• What is the direct cost of misallocation on economic growth?
• What are the policy implications?
Misallocation10

12. Summary of Findings
• Productivity gains arising from a reallocation of resources is estimated to be
95% between 2010. Moving towards the US level of efficiency in 1997 shows
productivity gains of about 36%.
- Productivity gains of 60-95%, in 2000, 2005 and 2010 – suggest the “catch-
up” process remains a challenge.
• By sector, misallocation seems more severe in selected resource-based
industries (food and beverage and petroleum and chemical industries) and less
so, in the textile, machinery, electrical and electronics and computers industries.
• Both distortions in the capital and output markets are important sources of
productivity losses.
• Productivity gains if realised, adds to +0.4 to +1.3 ppt to overall growth.
Misallocation11

13. An Overview of Hsieh and Klenow (2009)
Why is aggregate China and India’s TFPs are lower than US?
- Traditional explanations focus on barriers to technology diffusion
- Misallocation explanation focuses on inefficient use of resources
(licensing regulations, size-dependent policies, SOEs)
Main findings
- Larger gaps in China and India than US
- Can account for about half of aggregate TFP differences
- Shrinking gaps in China but not India
- Large plants have large marginal products in China and India
Misallocation12

14. Hsieh and Klenow (2009) Empirical Framework
Assumptions:
CES demand function, monopolistic competition and Cobb Douglas production
function
• Absence of distortion, firms in the same sector have the same “revenue
productivity”.
• Differences in “revenue productivity” across firms must be due only to
distortions.
Misallocation13

15. Hsieh and Klenow (2009): Empirical Framework (cont.)
Each firm in the sector s has a production function:
𝑌𝑠𝑖 = 𝐴 𝑠𝑖 𝐾𝑠𝑖
𝛼𝑠
𝐿 𝑠𝑖
1−𝛼𝑠
(1)
Each establishment maximises current profits:
𝜋 𝑠𝑖 = 1 − 𝜏 𝑌𝑠𝑖 𝑃𝑠𝑖 𝑌𝑠𝑖 − 𝑤𝐿 𝑠𝑖 − 1 + 𝜏 𝐾𝑠𝑖 𝑅𝐾𝑠𝑖 (2)
where 𝑃𝑠𝑖 𝑌𝑠𝑖 is the firm's value added, w and R are the cost of one unit of labour
and capital respectively. 𝜏 𝑌𝑠𝑖 denotes firm-specific output distortions and 𝜏 𝐾𝑠𝑖 is
"capital" distortions.
Misallocation14
FOC:
𝐾 𝑠𝑖
𝐿 𝑠𝑖
=
1
𝑅
𝛼 𝑠
1−𝛼 𝑠
𝑤 𝑠𝑖
1+𝜏 𝑘𝑠𝑖
(3)
As a result of the wedges, firms produce different amounts than what would have been
dictated by their different capital-labour ratios.

16. Differences between physical TFP (TFPQ) and revenue TFP (TFPR)
15 Misallocation
Hsieh and Klenow (2009) define their productivity measures as follows:
𝑇𝐹𝑃𝑄𝑠𝑖 = 𝐴 𝑠𝑖 =
𝑌 𝑠𝑖
𝐾𝑠𝑖
𝛼 𝑠 𝐿 𝑠𝑖
1−𝛼 𝑠
(4)
𝑇𝐹𝑃𝑅 𝑠𝑖 = 𝑃𝑠𝑖 𝐴 𝑠𝑖 =
𝑃 𝑠𝑖 𝑌 𝑠𝑖
𝐾𝑠𝑖
𝛼 𝐿 𝑠𝑖
1−𝛼 𝑠
(5)
• TFPQ captures “physical productivity" while TFPR measures “revenue
productivity".
• In the framework, if there are no distortions, TFPR does not vary across
plants (firms) within an industry:
𝑃𝑠𝑗 ∗ 𝐴 𝑠𝑗 = 𝑃𝑠𝑖 ∗ 𝐴 𝑠𝑖 = ⋯ (6)
- More capital and labor should be allocated to plants with higher TFPQ up to the point
where their higher output results in a lower price. Hence their TFPRs equal to TFPRs of
smaller plants.
• In the framework: 𝑇𝐹𝑃𝑅 𝑠𝑖 ∝ (𝑀𝑅𝑃𝐾𝑠𝑖) 𝛼𝑠
(𝑀𝑃𝑅𝐿 𝑠𝑖)1−𝛼𝑠

17. Firm-specific TFPR with Distortions
• For each firm, TFPR can be calculated as:
𝑇𝐹𝑃𝑅 𝑠𝑖 =
𝜎
𝜎−1
𝑅
𝛼 𝑠
𝛼 𝑠 𝑤
1−𝛼 𝑠
1−𝛼 𝑠 (1+𝜏 𝐾𝑠𝑖) 𝛼 𝑠
1−𝜏 𝑌𝑠𝑖
(7)
where 𝜏 𝑌𝑠𝑖 is output “wedge” ; 𝜏 𝐾𝑠𝑖 is capital “wedge”.
- If 𝜏 𝐾𝑠𝑖=0 and 𝜏 𝑌𝑠𝑖=0, TFPR is equalised for all firms in sector s
𝑇𝐹𝑃𝑅 𝑠𝑖 =
𝜎
𝜎 − 1
𝑅
𝛼 𝑠
𝛼 𝑠
𝑤
1 − 𝛼 𝑠
1−𝛼 𝑠
- If 𝜏 𝐾𝑠𝑖>0 and 𝜏 𝑌𝑠𝑖>0, TFPR is larger (i.e. the firm is “taxed” more)
Misallocation16
MC

18. TFP Loss from Resource Misallocation
𝑌 𝑎𝑐𝑡𝑢𝑎𝑙
𝑌 𝑒𝑓𝑓
= ς 𝑠=1
𝑆 σ𝑖=1
𝑀𝑠 𝐴 𝑠𝑖
𝐴 𝑠
𝑇𝐹𝑃𝑅 𝑠
𝑇𝐹𝑃𝑅 𝑠𝑖
𝜎−1
𝜃 𝑠
𝜎−1
(9)
If 𝜏 𝐾𝑠𝑖=0 and 𝜏 𝑌𝑠𝑖=0, 𝑇𝐹𝑃𝑅 𝑠=𝑇𝐹𝑃𝑅 𝑠𝑖. Hence, 𝑌𝑎𝑐𝑡𝑢𝑎𝑙= 𝑌𝑒𝑓𝑓: no TFP loss from
misallocation:
Misallocation17

19. Data Treatment
Malaysia
• We use census data in 2000, 2005 and 2010 to assess the changes in productivity
gains from better allocation of resources across time.
- Census of manufacturing firms
- Approximately 17,500 firms in 2000; 27,300 in 2005; and 33,800 in 2010
- 55 industries (3 digit MSIC codes) – before trimming
- Truncate data by setting >10 employees as a threshold
• Other data treatment issues
- Labour compensation (wages+ benefits), employment, value-added
- Capital stock = constructed from investment
- Drop firms with no capital stock or labour compensation data
- Drop industries which are represented by less than 9 firms
- Trim 1% tails to get rid of outliers in the sample
Firm Level Productivity Study18

20. Distribution of firms by size
Misallocation19
.4
.3
.2
.1
0
Density
0 2 4 6 8 10
Log employment distribution
2010 2005
2000
.4
.3
.2
.1
0
Density
2 4 6 8 10
Log employment distribution
2010 2005
2000
Distributions of firms in the three census
periods
Distributions of firms at the threshold of
>10 employees

21. Construction of Capital Stock
Initial capital stock, 𝐾0 calculated as:
𝐾0 =
𝐼 𝑜
(𝑑+𝑔)
(10)
Where
𝐼0 =
𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡
𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑎𝑙𝑢𝑒 𝑎𝑑𝑑𝑒𝑑
x value added at time t
𝑑 is the depreciation rate assumed to be 5%
𝑔 the growth rate of investment which is calculated from the data to be zero, in
other words, investment rate is constant across periods within a firm.
𝐾𝑡+5 = 𝐾𝑡−4 1 − 𝛿 + 𝐼𝑡+5 (11)
• The initial capital stock, 𝐾0 will be at the period which positive investment is
observed for a firm and therefore, the capital stock for the other periods will
either be iterated forward or backwards.
Equation (12) iterated backwards through repeated substitution of 𝐾𝑡−4
𝐾𝑡+5 = 𝐾0(1 − 𝛿)5
+ ҧ𝐼 (1 + 𝑔)(1 − 𝛿)4
+ ⋯ (12)
Misallocation20

22. Measurement/Calibration
Assigned parameters
• R=0.1 real rate 5%+ depreciation rate 5%
• σ=3 elasticity of substitution across producers in the same industry
• 1-α labour share in the corresponding US industry (*scaled up)
Inferred distortions
• 1+𝜏 𝐾𝑠𝑖=
𝛼 𝑠
1−𝛼 𝑠
𝑤𝐿 𝑠𝑖
𝑅𝐾 𝑠𝑖
capital wedge
• 1-𝜏 𝑌𝑠𝑖 =
𝜎
𝜎−1
1
(1−𝛼 𝑠)
𝑤𝐿 𝑠𝑖
𝑃 𝑠𝑖 𝑌 𝑠𝑖
output wedge
Misallocation21

23. A Large Proportion of Firms are in Non Resource Based Industries
and in Operations for > 6 years.
Misallocation22
Textile and apparel accounts for the largest
proportion of the firms (44%); followed by basic
metal and fabricated metal (17%).
The majority of firms are in operations for 6-15
years (38%); old firms accounted for 33%.
17.4
44.3
4.7
4.4
17.0
1.9
0.1
10.2
F&B Textile Wood
Petchem Metal M&E&C
Transport equip Others
Percent of firms by Industry, 2010* Percent of firms by age, 2010*
≤5 years,
29.1
≥6 to ≤15 years,
38.4
≥16 to ≤50
years, 31.9
>50 years,
0.7
≤5 years ≥6 to ≤15 years ≥16 to ≤50 years >50 years
*Note: applying >10 employees threshold

24. The Hypothetical Productivity Gains from Better Reallocation are
Estimated to be about 94%
23 Misallocation
 Productivity gains from the better allocation remained between 60-95% in 2000 -
2010. A declining productivity gains would suggest an improvement in the
distribution of resources over time.
 Distortions to capital improved while distortions to output worsen.
 Moving to the efficiency levels of the US 1997 was about 36% in 2010.
Year No. of
obs.
TFPQ TFPR Wedge P.H
Gain 1
P.H.
Gain 2
SD 75–25 90–10 SD 75–25 90–10 Capital
SD
Output
SD
2000 7,698 1.0537 1.5096 2.7399 0.7564 0.9414 1.8666 1.6637 0.5713 61.22 12.82
2005 9,511 1.0738 1.4774 2.7769 0.7813 0.9685 1.9440 1.6427 0.5681 80.81 26.53
2010 7,412 1.1385 1.5394 2.9679 0.7843 1.0017 1.9591 1.6220 0.6002 93.95 35.72

25. TFPQ and TFPR Dispersions
24 Misallocation
 TFPQ dispersions are getting slightly wider in 2010, less productive firms are getting even less
productive (left tail). The SD for TFPQ increased slightly to 1.14 in 2010, from 1.07 in 2005.
 TFPR dispersions also show a similar pattern, slightly wider dispersions in the left tail.
0
.2
.4
.6
Density
-3 -2 -1 0 1 2 3
TFPR distribution
2010 2005
2000
0
.1
.2
.3
.4
Density
-5 -4 -3 -2 -1 0 1 2 3
TFPQ distribution
2010 2005
2000

26. Malaysia has Similar Levels of Resource Misallocation as China
25 Misallocation
Source: Authors’ calculations (2017), Cirera et al (2017), Nguyen et al (2016) and Hsieh and Klenow( 2009)
% TFP gains % TFP gains
TFP Gains from Moving to US Efficiency LevelsTFP Gains from Efficient Allocation of Resources
42.9
78.0
86.6
93.9
127.5
162.6
0
20
40
60
80
100
120
140
160
180
US
1997
TUR
2014
CHN
2005
MYS
2010
IND
1994
KEN
2010
24.5
30.5
35.7
59.2
83.8
0
10
20
30
40
50
60
70
80
90
TUR
2014
CHN
2005
MYS
2014
IND
1994
KEN 2010

27. Malaysia’s Estimated TFPQ and TFPR Dispersions are Comparable to
Turkey and India
26 Misallocation
Source: Authors’ calculations; Nguyen, Taskin, and Yilmaz (2016); Hsieh and Klenow (2009).
Note: Number of firms: Malaysia (7,412); Turkey (22,148); China (211,304); India (41,006).
1.1
0.8
1.1
0.8
1.0
0.6
1.2
0.7
1.5
1.0
1.5
1.0
1.3
0.8
1.6
0.8
3.0
2.0
2.9
1.9
2.4
1.6
3.1
1.6
T FP Q T FP R T FP Q T FP R T FP Q T FP R T FP Q T FP R
M A LA Y S I A ( 2 0 1 0 ) T U R K E Y ( 2 0 1 4 ) C H I N A ( 2 0 0 5 ) I N D I A ( 1 9 9 4 )
N = 7 4 1 2 N = 2 2 1 4 8 N = 2 1 1 3 0 4 N = 4 1 0 0 6
SD 75-25 90-10

28. Higher Productivity Gains from Better Reallocation are Estimated for
the Resource-Based Industries
27 Misallocation
% TFP gains
Source: Authors’ calculation
0
50
100
150
200
250
Average TFP gains
F&B Petchem Metal M&E&C Wood Transport equip Textile Manufacturing

29. More Productive Firms Face Larger Distortions
28 Misallocation

30. Distortions in both Markets Appear to Affect Productivity
29 Misallocation
Productivity and Factor Market
Distortions
Productivity and Output Market
Distortions
Source: Authors’ calculation

31. Eliminating Distortions will Hypothetically Increase Growth by +0.4
to+1.3ppt
30 Misallocation
Source: Authors’ calculations and Eleventh Malaysia Plan (11MP).
Note: Top row = percentage point contribution to growth. Bottom row in brackets = percent contribution. 11MP = Eleventh Malaysia Plan; MA(3) = moving average
3; S1, S2, and S3 = Scenarios 1, 2, and 3, respectively; TFP = total factor productivity.
The assumption is that the manufacturing sector’s share of approximately 25% of the economy is also reflected in its share contribution to the aggregate TFP.
Calculated from the baseline growth of 5.8%.
Calculated from the baseline growth of 5%.
Baseline projections Baseline using 11MP Baseline using MA(3)
11 MP
(2016–20)
ARMA(p,q)
(2016–20)
S1 S2 S3 S1 S2 S3
Capital 2.6
(44.8)
2.2
(44.8)
2.6
(41.6)
2.6
(39.0)
2.6
(36.8)
2.2
(41.0)
2.2
(38.1)
2.2
(35.7)
Labor 0.9
(15.5)
0.8
(15.5)
0.9
(14.4)
0.9
(13.5)
0.9
(12.7)
0.8
(14.2)
0.8
(13.2)
0.8
(12.4)
Total factor
productivity
2.3
(39.7)
2.0
(39.7)
2.7
(44.0)
3.2
(47.5)
3.6
(50.4)
2.4
(44.8)
2.9
(48.7)
3.3
(51.9)
Gross domestic
product (%)
5.8 5.0 6.2 6.7 7.1 5.5 5.9 6.3
Additional
growth
+0.4a +0.9a
+1.3a +0.5b +0.9b +1.3b

32. Conclusion
31 Firm Level Productivity Study
• Malaysia shows relatively high dispersion in productivity of firms in the same
narrowly defined industry. This can be explained by misallocation of resources
across firms.
• Our estimates show that:
- Reducing distortions to the US level of efficiency could result in a
hypothetical aggregate productivity gain of 36%.
- A hypothetical productivity gain of 94% is estimated if distortions are
completely removed.
- Productivity gains are quite comparable with other upper-middle income
countries.
- Food and beverage firms operate in the most distorted market conditions.
- Both the input and output market distortions constrain productivity
• Broadly, there should be efforts to increase domestic competition and reduce
non-performance-based incentives.
• But, further investigation is needed to pin the sources of distortions.
• Results highlight the need to maintain the efforts to further ingrain productivity at
the core of policy making in Malaysia.

33. 32 Firm Level Productivity Study
Thank You