Tail Winds from the East? The Effect of Emerging Markets on UK - - PowerPoint PPT Presentation

John Lewis Jumana Saleheen 20th September 2013

The Effect of Emerging Markets on UK import prices Tail Winds from the East?

Disclaimer: Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the Bank of England or to state Bank of England policy. This paper should therefore not be reported as representing the views of the Bank of England or members of the Monetary Policy Committee or Financial Policy Committee.

Motivation

• Widespread claims that “cheap imports“ from low-wage

producers have reduced inflationary pressure. “For a number of years, the United States and other industrialized nations benefited from disinflation in manufactured goods produced in EMEs. This shift in relative prices—a positive terms of trade gain—helped contain inflation.”

• William Dudley, President New

York Fed

• Did the growth of imports from emerging market economies help

contain inflationary pressure in the UK during the long expansion?

Imports from low cost producers: manufacturing

• China has shown a larger increase (≈10.5pp) than other LWCs (≈2.5pp)
• r NMS (≈5pp)

2 4 6 8 10 12 14 1999 2001 2003 2005 2007 2009 2011 % of manufacturing imports China LWC NMS

Cost advantage of selected EMEs

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 China Vietnam Pakistan India Russian Thailand Philippines Indonesia Turkey Mexico Brazil Bulgaria Romania Lithuania Poland Latvia Hungary Czech Rep Estonia Slovakia Slovenia Ratio of PPP to market exchange rate, average 1999-2011

Possible Channels

+ Beneficial terms of trade shock lowers import prices:“price level effect”

– Direct effect of more “cheap imports” from EMEs – Indirect competition effect on non-EMEs

+ Competition from cheap imports may also put downward pressure on domestic producers prices – But rising costs in “low-wage” producers can be a “headwind”: “inflation effect”

– Greater exposure to countries with rising costs generates inflationary pressure

– EMEs may have pushed commodity prices up Caution about effect of lower import prices on CPI inflation i) Relative price shock may not feed through to overall prices ii) “Tailwind” could be that domestic economy is run at a high rate of growth than could otherwise be possible

Related Literature: Impact on domestic producers

Effect on import prices: Kamin et al (2006) regress change in China’s market share on import

• prices. (But only two time periods 1993 and 2001)

McCoille (2008): Simple accounting approach (no allowance for competition effects on other countries exporters) Pain et al (2006) + Nickell (2005): Mechanistic estimate based on relative price level and increase in shares (again no competition effects) Wheeler (2008): Regression based approach (but for limited number of sectors)

Overview

Our Empirical Analysis

• Uses data on the volume and value of UK imports in over 3000 goods categories over the

period 1999-2011 to estimate panel regressions of EME effect on import prices

• Allow for cross sectional dependence in the error term, and use dataset with much richer

cross sectional and time series dimensions than most existing studies.

• We show that allowing for differences in coefficients across sectors can lead to larger

estimates of the effect of Chinese market share.

• 4 key questions

– Did growth of low cost producers reduce import prices? China yes, others no – How big is it? -0.92pp in manufacturing (= -0.63pp per year overall) – Has this effect changed over time? No sign of drop-off so far – Has higher inflation in low cost producers fed through to UK import prices: No Putting this in the broader context

• How do our results compare with the rest of the literature: Bigger downward pressure, but

still relatively small

• Effect of EMEs on commodity prices: Hard to quantify but may have offset tailwind

Dataset: Imports

• Import data taken from UK Customs (HMRC) Tradeinfo

database, containing volumes and values of imports by trading partner and industry over the period 1999-2011

– Restricted to 45 countries to keep dataset computationally manageable

• EU, OECD, plus Brazil, China, Hong Kong, Indonesia, India, Mexico,

Philippines, Pakistan, Russia, Singapore, Thailand, Turkey, Vietnam

• Around 90% of UK imports

– More than 3000 industries using Standard Industrial Trade Classification (SITC) at 5-digit level – Raw data contains nearly 2 million datapoints

5-digit code Industry Name

• No. of inds

8853x WRIST WATCHES, POCKET WATCHES AND OTHER WATCHES (INCLUDING STOP WATCHES) WITH CASE OF PRECIOUS METAL OR METAL CLAD WITH PRECIOUS METAL 3 8854x WRIST WATCHES, POCKET WATCHES AND OTHER WATCHES (INCLUDING STOP WATCHES), WITH CASES NEITHER OF PRECIOUS METAL NOR CLAD WITH PRECIOUS METAL 3 8855x WATCH MOVEMENTS, COMPLETE AND ASSEMBLED 2 8857x CLOCKS 9 8859x TIME MEASURING EQUIPMENT AND ACCESSORIES, N.E.S.; PARTS AND ACCESSORIES FOR CLOCKS 9 5-digit code Industry Name

• No. of inds

88571 INSTRUMENT PANEL CLOCKS AND CLOCKS OF A SIMILAR TYPE, FOR VEHICLES, AIRCRAFT, SPACECRAFT OR VESSELS 1 88572 CLOCKS WITH WATCH MOVEMENTS (EXCLUDING INSTRUMENT PANEL CLOCKS), BATTERY POWERED 1 88573 CLOCKS WITH WATCH MOVEMENTS (EXCLUDING INSTRUMENT PANEL CLOCKS), OTHER THAN BATTERY POWERED 1 88574 ALARM CLOCKS (WITH CLOCK MOVEMENTS), BATTERY, OR AC POWERED 1 88575 ALARM CLOCKS (WITH CLOCK MOVEMENTS), N.E.S. 1 88576 WALL CLOCKS (WITH CLOCK MOVEMENTS), BATTERY, OR AC POWERED 1 88577 WALL CLOCKS (WITH CLOCK MOVEMENTS), N.E.S. 1 88578 CLOCKS (WITH CLOCK MOVEMENTS), N.E.S., BATTERY OR AC POWERED 1 88579 CLOCKS (WITH CLOCK MOVEMENTS), N.E.S. 1

Intermezzo: SITC System

• Each industry has 5-digit code:

– e.g. “Battery/AC powered alarm clocks”: 88574 – First digit denotes broadest classification – Subsequent digits give finer levels of disaggregation

5-digit code Industry Name

• No. of inds

0xxxx FOOD AND LIVE ANIMALS 346 1xxxx BEVERAGES AND TOBACCO 22 2xxxx CRUDE MATERIALS, INEDIBLE, EXCEPT FUELS 277 3xxxx MINERAL FUELS, LUBRICANTS AND RELATED MATERIALS 41 4xxxx ANIMAL AND VEGETABLE OILS, FATS AND WAXES 46 5xxxx CHEMICALS AND RELATED PRODUCTS, N.E.S. 487 6xxxx MANUFACTURED GOODS CLASSIFIED CHIEFLY BY MATERIAL 837 7xxxx MACHINERY AND TRANSPORT EQUIPMENT 682 8xxxx MISCELLANEOUS MANUFACTURED ARTICLES 444 9xxxx COMMODITIES AND TRANSACTIONS 13 5-digit code Industry Name

• No. of inds

81xxx PREFABRICATED BUILDINGS; SANITARY, PLUMBING, HEATING & LIGHTING FIXTURES AND FITTINGS, N.E.S. 17 82xxx FURNITURE AND PARTS THEREOF; 23 83xxx TRAVEL GOODS, HANDBAGS AND SIMILAR CONTAINERS 9 84xxx ARTICLES OF APPAREL AND CLOTHING ACCESSORIES 99 85xxx FOOTWEAR 19 87xxx PROFSSIONAL, SCIENTIFIC AND CONTROLLING INSTRUMENTS AND APPARATUS, N.E.S. 66 88xxx PHOTOGRAPHIC APPARATUS, EQUIPMENT & SUPPLIES & OPTICAL GOODS, N.E.S.; WATCHES AND CLOCKS 60 89xxx MISCELLANEOUS MANUFACTURED 151 5-digit code Industry Name

• No. of inds

881xx PHOTOGRAPHIC APPARATUS AND EQUIPMENT, N.E.S. 15 882xx PHOTOGRAPHIC AND CINEMATOGRAPHIC SUPPLIES 6 883xx CINEMATOGRAPHIC FILM, EXPOSED AND DEVELOPED, WHETHER OR NOT INCORPORATING SOUND 2 884xx OPTICAL GOODS, N.E.S. 11 885xx WATCHES AND CLOCKS 26

Basic Regression Setup

• In keeping with Kamin et al, we clean up the dataset:

– Any unit value inflation of more than 900% or below -90% is dropped

• Standard panel form used in the literature:

– Country and time fixed effects – Robust standard errors, clustered w.r.t. i

• X is a vector of within period averages of each explanatory

variable, calculated for each 4-digit industry, similar in spirit to Kapetanios et al (2011)

it t i it LWC it LWC it NMS it NMS it CHINA it CHINA it it

e S S S S S S                           

  

X ψ'

2 1 1 2 1 1 2 1 1

Total Effect

• Given earlier results, we focus on effect of China
• Total effect of China across all manufacturing industries is:
• Aggregation effects may be important if more than one of the following holds:

– If β differs across industries – If the change in China’s market share differs across industries – The relative weights of the industries differs across time

• Compute measure under different assumptions about β

– Common across all industries – Common within 1-digit industry group (separate regressions for each 1d ind) – Common within 2-digit industry group (separate regressions for each 2d ind)

• .



 

i CHINA it i it it

S w Total 

Effect of China at different levels of disaggregation (manufacturing)

• 1.6
• 1.1
• 0.6
• 0.1

0.4 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 China Effect, pp on manufacturing import price inflation Common β across all industries Common β within each 1 digit industry Common β within each 2 digit industry

• Poolability test:

– Common vs 1-digit: p-value 0.000; 1-digit vs 2-digit: p-value 0.000

Bootstrapping a confidence interval for the price- level effect (China)

Tail Winds from the East? 4th May 2012

• 2.50
• 2.00
• 1.50
• 1.00
• 0.50

0.00 2000 2002 2004 2006 2008 2010 pp 95% CI Mean

Bootstrapping the Inflation Effect (China)

Tail Winds from the East? 4th May 2012

• 6.00
• 5.00
• 4.00
• 3.00
• 2.00
• 1.00

0.00 1.00 2000 2002 2004 2006 2008 2010 pp 95% CI Mean

Tail Winds from the East? 4th May 2012

LWC: Price level effect NMS: Price level effect LWC: Inflation effect NMS: Inflation Effect

• 1.00
• 0.50

0.00 0.50 1.00 1.50 2.00

2000 2002 2004 2006 2008 2010 pp

95% CI Mean

• 5.00
• 4.00
• 3.00
• 2.00
• 1.00

0.00 1.00 2.00

2000 2002 2004 2006 2008 2010 pp

95% CI Mean

• 5.00
• 4.00
• 3.00
• 2.00
• 1.00

0.00 1.00 2.00

2000 2002 2004 2006 2008 2010 pp

95% CI Mean

• 2.00
• 1.00

0.00 1.00 2.00 3.00 4.00

2000 2002 2004 2006 2008 2010 pp

95% CI Mean

Estimating the indirect effect

• Calculate measure of unit value inflation over non-Chinese

producers, πEXC

• Estimate regression:
• Coefficient on the change in China’s share gives the effect of

Chinese entry on competitors prices

• As before, run regression at 2-digit industry level, so allow for

coefficients to vary across product types

• Using coefficients, can then back out competition effect; direct effect

given by total effect minus competition effect

it t i it LWC it LWC it NMS it NMS it CHINA it CHINA it EXC it

e S S S S S S                           

  

X ψ'

2 1 1 2 1 1 2 1 1

China: Direct vs Indirect Effect (manuf, 2d coeffs)

• Around 2/3 of effect is the direct effect, around 1/3 is competition
• 1.6
• 1.4
• 1.2
• 1.0
• 0.8
• 0.6
• 0.4
• 0.2

0.0 0.2 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Effect on Manufacturing Import Price Inflation, pp Direct effect Competition effect

Robustness checks

Tail Winds from the East? 4th May 2012

• 1.8
• 1.6
• 1.4
• 1.2
• 1
• 0.8
• 0.6
• 0.4
• 0.2

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AVERAGE Effect on inflationary pressure, pp Benchmark No fixed effects No 4d averages Omitting NMS+Others Include LDV Recode insig coeffs

Other estimates of China price level effect

Tail Winds from the East? 4th May 2012

Country Author(s) Sample period Estimated effect, per annum, pp Import price inflation

• Manuf. import

price inflation HICP inflation US Kamin et al (2008) 1993-2001

• 0.53

US Pain et al (2008) 2001-2005

• 0.12

OECD Kamin et al (2008) 1993-2001

• 0.13

€A ECB (2006) 1995-2005

• 1

€A Pain et al (2006) 2001-2005

• 0.19

UK Kamin et al (2008) 1993-2001 UK McCoille (2008) 1999-2006

• 0.5

UK Nickell (2005) 1999-2005

• 0.55

UK Wheeler (2008) 1990-2004

• 0.5
• 0.35

UK Pain et al (2006)* (non-OECD Asia) 2000-2005

• 0.2 to -0.3

UK Lewis/Saleheen 1999-2011

• 0.60
• 0.87

≈-0.20

Other estimates of NMS/LWC effect

Tail Winds from the East? 4th May 2012

Country Author Sample period Estimated effect, per annum, pp Import price inflation Manuf. import price inflation HICP inflation €A ECB (2006) 1995-2005

• 1.0

UK Lewis/Saleheen 1999-2011

• 0.20 (insig)
• 0.28 (insig)

≈-0.07 NMS

Why only China depressing prices?

• NMS enjoyed only slightly smaller cost advantage than China
• Rate of market share accquisition around half that of China
• Consistent with Auer et al (2012): no evidence that NMS gaining

import market share put downward pressure on domestic producers prices.

• LWC gained market share at a much slower speed than China

(2.5pp vs 10.5pp) over 12 year sample period

• Compared to the US, LWCs account for much lower proportion of

growth in EME market share.

What other channels might have been at work?

Upward pressure on commodity prices?

• EMEs account for virtually all of rise

in demand for commodities since 2000

• IMF (2011) estimates around 20% of

rise in crude oil price since 2004 is due to China

• OECD (2006): If non-OECD

countries had held market share at 2000 levels, oil prices 40% ($35) lower by end 2005.

• Pain et al (2006), estimate impact on

UK CPI, 0.1%pp pa 1995-2005

• 20
• 10

10 20 30 40 50 60 70 80 Oil Coal Copper Aluminium China Other EMEs Advanced economies Total world Change between 2000 and 2012, per cent

What other channels might have been at work?

Impact on domestic producers prices?

• Auer and Fischer (2010) + Auer et al (2012) find strong effect of

Low wage import competition on domestic producers in US and Europe

• PPI effect estimated to be -0.5pp pa for US (no figure for Europe)
• Compressed margins, spurred productivity gains, but above all

lowered wages

Conclusions

• Low cost imports from China have lowered inflationary pressure

– Around 0.87pp per year for manufacturing sector // 0.63pp overall

• New member states have had some effect, Low wage countries little effect
• Our estimate is at or near the top of the range found by other work, but still

relatively modest even if it translates to CPI inflation with no relative price offsets.

• Given possible offset from higher commodity effects, overall effect on import

prices small or neutral, but could even have been net positive for inflationary pressure

• No evidence that China effect has diminished over time

– Splitting sample w.r.t. to time and Chinese market share yields similar results

• We don’t see higher inflation in low cost producers feeding through to import

prices