Parallel Universes

Presentation to EERC Workshop

Kyiv, May 2016

John S Earle

GMU School of Policy and Government

Dashing from one thing to another, or linking them together, he

heaped them up – first because he had endless things in his head,

and one thing led on to the next; but in particular because it was

his passion to make comparisons and discover relations, display

influences, lay bare the interwoven connections of culture.

-- Thomas Mann, Doctor Faustus

Parallel Universes

Two examples of EERC-inspired collaborations and research

Wage arrears

– Klara Sabirianova Peter

– Reactions to Hartmut Lehmann, Mark Schaffer, Layard, etc.

Productivity, reallocation, and misallocation

– David Brown

– Inspiration from Rick Ericson, others

– Reaction to Bartelsman-Haltiwanger-Scarpetta, Hsieh-Klenow, etc.

Today’s Scripture(Deuteronomy 24: 14-15)

“You shall not withhold the wages of poor and needy laborers, whether other Israelites or aliens who reside in your land in one of your towns. You shall pay them their wages daily before sunset, because they are poor and their livelihood depends on them; otherwise they might cry to the Lord against you, and you would incur guilt.”

Defining Institutions:Conventional Economic Approaches

Organizations (e.g., unions)

Policies (e.g., welfare system)

Non-market constraints / Rules

“Institutions include any constraints devised to shape human interaction.” “Major role of institutions is to reduce uncertainty…” (North, 1990)

– Intentionality

– Functionalism

Equilibrium strategy in a game (Aoki, 2005)

Elements of a Comparative Institutional Analysis

Complementarities; feedback

Path-dependence; history matters

Increasing returns; network externalities

Sunk costs; lock-in

Endogenous enforcement

Institutional independencies in multiple spheres (“linked domains” – Aoki, 2005): labor, finance, suppliers, politics, culture

Related Sub-Fields of Economics

Technology adoption and standards– David 1985, Katz & Shapiro 1986, Arthur 1989

Coordination failures– Diamond 1982, Cooper & John 1988, Murphy et al

1989, Azariadis & Drazen 1990)

Social interactions– peer effects (Evans et al. 1992, Sacerdote 2001)

– neighborhood effects (Katz et al 2001, Kling et al 2005)

– crime (Sah 1991, Glaeser 1996)

– labor supply (Woittiez & Kapteyn 1998, Weinberg et al 2004, Grodner & Kniesner 2006)

Social Interactions: Theory and Econometrics

Models of Interactions

– Theory (Durlauf & Young 2001, Glaeser & Scheinkman 2004)

– Customs, conventions, conformity (Akerlof1980, Young 1993, Bernheim 1994)

– Strategic complementarities (Bulow et al. 1985, Milgrom & Roberts 1990)

Econometrics: “the reflection problem”

Manski 1993, Brock&Durlauf 2001, Moffitt 2001

Econometrics of Identifying/Measuring Institutions

Sociology

– Organization-level; linear in lagged mean regression

Economics: focus on identification problems

– Individual-level (social interactions)

– Reflection problem (Manski 1993)

– Experiments vs. policy interventions (IV)

No estimates of feedback mechanisms

Few of non-linear models or multiple equilibria

Need case with special characteristics and data

– Especially interesting is a pernicious practice

A Case Study of an Institution

Equilibrium outcome of a game (Aoki)

Strategic complementarities

Linked domains: economic, social, organizational, governance, legal, political, financial, cognitive, norms, discourse/rhetoric

Multiple equilibria – under some conditions

Other factors: geography, macro (volatility), international

Example from transition economy

Microdata (linked employer-employee) for estimation

Complementarities identified through policy intervention

Measurement of 4 feedback loops that sustain equilibrium

Estimates of 3 equilibria

Research on Wage Arrears

“How Late to Pay? Understanding Wage Arrears in Russia” (with Klara Sabirianova), Journal of LaborEconomics, 2002.

“Complementarity and Custom in Wage Contract Violation” (with Klara Sabirianova Peter). Review of Economics and Statistics, 2009.

“The Normalization of Deviant Organizational Practices: Wage Arrears in Russia, 1992-1999” (with Andrew Spicer and Klara Sabirianova Peter). Academy of Management Journal, April 2010.

Wage Contracts and Wage Arrears: Definitions

Wage contract: employee works and employer pays an agreed wage at an agreed time

Wage arrears: breach of contract where employer fails to pay in full and/or on time

The Puzzle of Wage Arrears (WA)

In most economies, breaches of wage contracts are rare:

– fundamental economic institution, taken for granted– exceptions: fraud, start-ups, bankruptcies

But in some economies at some times WA are large.Russia:

– widespread (64% of workers at end-1998)– large magnitude (average conditional stock = 4.8 months)– persistent (since 1992)– pervasive most sectors, ownership types, industries, regions,

labor force groups affected – although unevenly– most prevalent not in small firms or start-ups, but in the large

enterprise, formal sector– social and political consequences – WA frequently ranked as the

No. 1 social problem in Russia, yet few large-scale protests

The Puzzle of Wage Arrears

Not an intrinsic feature of transition

– Countries not affected (accumulated wage debt <1% of GDP) – Belarus, Czech Republic, Estonia, Hungary, Lithuania, Poland, Slovakia, Slovenia

– Countries moderately affected (1-3% of GDP) – Armenia, Bulgaria, Kyrgyzstan, Latvia, Romania, Tajikistan

– Countries severely affected (3-10% of GDP) – Croatia, Kazakhstan, Moldova, Russia, Ukraine

Why is the practice usually so rare, but sometimes might be so common and persistent, as in Russia?

Hypothesis: complementarity and custom

Conventional Economic Accounts of Wage Arrears in Russia: “Flexibility” in response to distress

Layard and Richter (1994): WA are a form of ”wage flexibility... explained by the willingness of workers to accept pay cuts in order to preserve jobs.” Wage flexibility makes the Russian labor market “every neoclassical economist's dream.“

OECD (1995) praises the “remarkable flexibility...of real wages” and the use of “wage arrears...to finance this employment surplus.”

Similar but less sanguine: Clarke (1996), Gimpelson(1998, also redistributive), Lehmann et al. (1998)

Alfandari and Schaffer (1996): “Accounting fiction” since managers could just lower the wage they actually pay

WA as part of the market?

Desai and Idson (1998): WA ”enforce downward wage flexibility,” explained by “market considerations” (negative W-WA rel)

Boris Yeltsin: striking miners with WA “have not yet learned to work in a market economy.”

– “They do not want to listen to any sober arguments or reasonable explanations. They want their problems settled immediately, which means at the expense of someone else. Who should the government take the money away from? Maybe from pensioners, students, doctors, teachers, and metallurgy workers? Do they need money less than miners?”

An Alternative Approach: Understanding Wage Arrears as an Institution

Special factors have raised incentives of employers to pay late and the tendency for employees to tolerate late payment

Increasing returns to payment practices within (local) labor markets:– strategic complementarities across employers

– social interactions across workers

– endogenous legal regime

Possibility of multiple equilibria: – “WA equilibrium” or “contract violation equilibrium”

– “punctual payment” or “honored contract equilibrium”

Empirical Observations to be Explained

Large arrears even at firms showing strong growth and liquidity performance

Persistence of substantial delays over time

Large geographic variation in level of arrears

Geographic variation in workers’ tolerance

Strategic Complementarities and Neighborhood Effects

Responses to WA

1. Workers quit

2. Reduction in effort/hours (“if you don’t pay your servant his wages, he will pay himself” – Spanish proverb)

3. Strikes/protests

4. Legal penalties

Firm using WA creates an externality for other firms considering a WA strategy:

1. reduces attractiveness of quitting

2. reduces negative effort response

3. reduces strike threat

4. reduces legal penalties (“Of what use are laws empty of customs?” – Horace)

Strategic Complementarities and Neighborhood Effects

Firm using WA creates an externality for other firms:1. reduces attractiveness of quitting in response to WA2. reduces negative effort response3. reduces strike threat4. reduces legal penalties (congestion, social norms)

WA may be strategic complements

The practice may have multiple equilibria

When a critical mass of employers in a local area does not pay on time, it becomes optimal for most/all other employers in the region also not to pay. When a critical mass does pay, it is optimal to pay.

Formal Model => Possibility of multiple equilibria (symmetric Nash with

identical players conditional on observables)

1*=1*

Unstable

Equilibrium

(2*)

Late-Payment

Equilibrium

(3*)

Punctual -

Payment

Equilibrium

(1*)

2*=2* 3*=3

*

Equilibrium Selection

What gave rise to the WA equilibrium in many parts of Russia?

Some big player in the labor market?

Our conjecture: the state set the standard

Government attempts to balance the budget through sequestration

Rule of law sacrificed to macro policy

Initial Evidence

Firm survey (527 industrial employers, 196 farms)

Comparison of average WA in declining and growing firms

WA in top quartile of growing firms

Probability of location in a high-WA region for firms with WA and without, declining and growing

Wage Arrears by Growth and Liquidity of Firms, 1998

Growth and

Liquidity Measures

Definition of

Expanding/Liquid

Firms

Mean Wage Arrears

Declining

Firms E(Wi|Gi<0)

Expanding

Firms E(Wi|Gi>0)

t-test for

difference E(Wi|Gi>0) –

E(Wi|Gi<0)

Best

Firms E(Wi|Gi >

Gi+.75

)

Sales Positive sales

growth

2.696a

(0.191)

[314]

2.528a

(0.355)

[96]

0.423

2.965a

(1.022)

[23]

Output Positive output

growth

2.551a

(0.180)

[356]

2.687a

(0.319)

[98]

-0.357

3.188a

(0.819)

[24]

Real wages Increase in real

wages

2.526a

(0.181)

[308]

2.897a

(0.365)

[116]

-1.006

3.231a

(0.897)

[26]

Nominal wages Increase in nominal

wages

3.390a

(0.316)

[135]

2.271a

(0.188)

[289]

3.198a

2.587a

(0.501)

[70]

Employment Increase in

employment

3.063a

(0.202)

[321]

1.716a

(0.219)

[146]

4.032a

1.649a

(0.303)

[37]

Hiring rate Hiring rate above

the median

3.193a

(0.271)

[207]

2.358a

(0.213)

[205]

2.416b

2.510a

(0.287)

[103]

Profitability

(profit/output)

Positive profit 4.001a

(0.286)

[201]

1.580a

(0.145)

[253]

7.993a 1.591

a

(0.340)

[64]

Received patents

(dummy)

Received patents 2.191a

[402]

1.704a

[72] 1.314 -

Frozen bank account

(dummy)

Account not frozen 3.515a

[349]

0.812a

[196] 9.765

a -

Barter in payments

for inputs (dummy)

No barter payments

for inputs

2.739a

[348]

2.538a

[103] 0.554 -

Barter in sales

(dummy)

No barter received

for sales

2.801a

[379]

2.300a

[100] 1.369 -

Overdue receivables

(dummy)

No overdue

receivables

3.236a

[318]

1.274a

[105] 5.129

a -

Overdue payables

(dummy)

No overdue

payables

3.291a

[320]

1.050a

[102] 5.840

a -

Percentage of Firms in High Wage Arrear Regions by Growth and Liquidity of Firms, 1998

Growth and Liquidity

Measures

Declining Firms (Gi < 0) Expanding Firms (Gi > 0)

Wi = 0 Wi > 0 Wi = 0 Wi > 0

Prob(Ωi > Ωmed | Gi, Wi)

Sales 41.7

[120]

72.2

[194]

28.6

[35]

68.9

[61]

Output 37.9

[140]

70.8

[216]

25.0

[36]

66.1

[62]

Real wages 36.1

[119]

67.2

[189]

29.6

[44]

75.0

[72]

Nominal wages 29.3

[41]

67.0

[94]

36.1

[122]

70.7

[167]

Employment 38.0

[100]

69.7

[221]

30.4

[79]

68.7

[67]

Hiring rate 34.3

[73]

71.6

[134]

39.2

[79]

65.9

[126]

Profitability (profit/output) 43.8

[48]

72.6

[153]

33.1

[127]

69.1

[126]

Received patents (dummy) 31.8

[170]

69.8

[232]

36.8

[38]

64.7

[34]

Frozen bank account

(dummy)

33.3

[69]

69.6

[280]

35.5

[155]

68.3

[41]

Barter in inputs (dummy) 37.2

[121]

67.8

[227]

29.3

[41]

75.8

[62]

Barter in sales (dummy) 39.8

[128]

68.1

[251]

22.2

[45]

72.7

[55]

Overdue receivables

(dummy)

38.0

[92]

69.9

[226]

34.8

[69]

69.4

[36]

Overdue payables (dummy) 39.4

[94]

69.5

[226]

30.9

[68]

70.6

[34]

Estimated Reaction Functions of Wage Arrears

0

1

2

3

4

5

6

7

8

9

10

11

12

0 1 2 3 4 5 6 7 8 9 10 11 12

Local wage arrears, months

1994-2000

1996-2000

Do WA remain on the menu? Regional patterns in 2009 vs. 2000

0.1

.2.3

0 .1 .2 .3 .4 .5 .6 .7 .8 .99-year lag

Fraction of employees with WA, 2009

Continuity in Patterns of WA

0.1

.2.3

.4.5

.6.7

.8.9

1

0 1 2 3 4 5 6 711-year lag

Unconditional number of owed months, 2009

Productivity, Reallocation, and Misallocation

Reallocation is a basic issue in market economies Inherited misallocation => importance for transition Brown and Earle (every year since 2000) “Misallocation and Productivity Dispersion: A Theoretical

and Empirical Analysis” (with Brown and Emin Dinlersoz, 2016)

Any opinions and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information on individual firms is disclosed.

Productivity Dispersion

Substantial TFP dispersion measured even within narrow industries:– Dhrymes (1991)

– Bartelsman and Doms (2000)

– Dunne et al. (2004)

– Syverson (2004): 90-10 ratio ~ 2 for TFP, ~3 for LP

– Foster et al. (2008)

– Bartelsman et al. (2013)

Is this inefficient?

What prevents productivity equalization?

What prevents productivity equalization?

One idea: static distortions = idiosyncratic taxes on output or inputs (Restuccia-Rogerson 2008; Hsieh-Klenow 2009) If static distortions are reduced, productivity

dispersion falls and average productivity rises Conclusion: reforms/liberalization reduce dispersion Aggregate TFP gains from equalizing TFP within

industries: China 2005: 87% India 1994: 128% U.S. 1997: 43% (but only 30.7% in 1987)

An Alternative Explanation

Reallocation frictions– sunk costs of entry– fixed operating costs– costs of investment with stochastic outcomes

Models of industry dynamics– Jovanovic (1982), Hopenhayn (1992), Ericson and Pakes

(1995)

Reducing frictions may not lower productivity dispersion

Dispersion reflects experimentation and selection mechanisms

Two types of experimentation: entry, restructuring

Model: Contrast with Hsieh-Klenow

HK assume imperfectly elastic demand, and price is a fixed markup over marginal cost (inversely proportional to TFPQ)

Firms with higher TFPQ produce a higher quantity, but charge a lower price

Absent static distortions, TFPR is equalized across firms, and there is no TFPR dispersion

Static distortions (idiosyncratic taxes) create dispersion

Sketch of Model

– Continuum of firms produce a homogeneous good

– Discrete time, multiple periods

– Firms take input and output prices

– Heterogeneous TFPQ, evolving independently for each firm

– Fixed cost of operating in industry

– Potential entrants have priors about on post-entry productivity. Pay entry cost, and initial TFPQ is revealed.

– Incumbent firms may invest/restructure to achieve potential improvements in TFPQ

Data

U.S. Census of Manufactures (1963, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002, and 2007)

Official data on manufacturing firms in Eastern Europe– Georgia (Statistical Dept.): 2000-2004, 2,645 firms

– Hungary (Tax Authority): 1986-2005, 50,069 firms

– Lithuania (Statistics Lithuania): 1995-2005, 8,037 firms

– Romania (Nat. Statistics Comm., Finance Min.): 1992-2006, 77,535 firms

– Russia (State Statistical Committee): 1985-2005, 41,029 firms

– Ukraine (State Statistical Committee): 1989, 1992-2006, 47,881 firms

Data

U.S. Telecommunications Equipment analysis uses MFP including capital (perpetual inventory method, separately for structures and equipment), labor (total hours), energy, and other materials, using factor cost shares method, and LP (value added per hour worked)

Analysis including Eastern European firms uses MFP calculated as residual from Cobb-Douglas production function with capital stock and number of workers, estimated separately for 19 NACE 2-digit sectors

Evolution of MFP Dispersion in the U.S. Telecommunications Equipment Sector

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1972 1977 1982 1987 1992 1997

Log

MFP

Sta

ndar

d De

viat

ion

Telecom Equip. All Manufacturing

Evolution of LP Dispersion in the U.S. Telecommunications Equipment Sector

0

0.2

0.4

0.6

0.8

1

1.2

1963 1967 1972 1977 1982 1987 1992 1997

LP S

tand

ard

Devi

atio

n

Telecom Equip. All Manufacturing

MFP Distribution in the U.S. Telecommunications Equipment Sector

Effects of Entry, Exit, and Continuers on 5-Year MFP Standard Deviation Change in the U.S. Telecommunications Equipment Sector

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

0.12

1977 1982 1987 1992 1997

Diffe

renc

e in

MFP

Sta

ndar

d De

viat

ion

Entry Effect Exit Effect Continuer Effect

EBRD Market Institution Index

1

1.5

2

2.5

3

3.5

4

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

EBRD

Mar

ket I

nstit

utio

ns In

dex

Georgia

Hungary

Lithuania

Romania

Russia

Ukraine

Evolution of Productivity Dispersion with Market Liberalization

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Sta

nd

ard

De

via

tio

n o

f M

FP

Georgia

Hungary

Lithuania

Romania

Russia

Ukraine

U.S.

Productivity Distribution Prior to Transition to Market Economy

Productivity Distribution During Transition to Market Economy

New Entrant Productivity Distribution

0

5

10

15

20

25

<-1.5 -1.5 --1

-1 - -0.75

-0.75- -0.5

-0.50- -

0.25

-0.25- 0

0 -0.25

0.25-

0.50

0.50-

0.75

0.75- 1

1 -1.5

>1.5

Perc

enta

ge o

f Age

1 F

irm

s

MFP Range

Georgia 2001-04

Hungary 1993-2003

Lithuania 1996-2005

Romania 1993-2006

Russia 1993-2005

Ukraine 1993-2006

U.S. 1977-2007

Productivity and Exit Rates

0

5

10

15

20

25

30

<-1.5 -1.5 --1

-1 - -0.75

-0.75- -0.5

-0.50- -

0.25

-0.25- 0

0 -0.25

0.25-

0.50

0.50-

0.75

0.75- 1

1 -1.5

>1.5

Pro

po

rtio

n E

xiti

ng

MFP Range

Georgia 2001-04

Hungary 1987-1989

Hungary 1993-2003

Lithuania 1996-2005

Romania 1993-2006

Russia 1993-2005

Ukraine 1993-2006

U.S. 1977-2007

Conclusion

HK’s “TFP Gains from Equalizing TFPR” in the

US: 36% in 1977, 31% in 1987, 43% in 1997

Notice the fluctuation across periods, plus:

Output rose only 15% 1977-87 but 40% 1987-97

No simple relationship between policies,

institutional quality, and productivity dispersion

Experimentation dominates selection

Conclusions (1/3)

Interactions-based models always face identification problems– This research provides:

Explicit analyses of four feedback loops Valid IVs from exogenous decisions in the public sector Nonlinear estimates of reaction function, multiple equilibria

Many studies discuss the importance of reliable contracting for economic development but little research on factors sustaining or undermining contracts– This research provides:

Analysis of mechanisms that may lead to breakdown of contract enforcement, sustainability of the “bad equilibrium”

Demonstration of government role in contract enforcement

Conclusions (2/3)

Wage payment practices as institutions

Strategic complementarities in firm behavior

Neighborhood effects in worker behavior

Linked domains (Aoki): labor, social, organizational, governance, legal, political, financial, cognitive, norms, discourse/rhetoric

Multiple equilibria – parallel universes

Conclusions (3/3)

Wage payment practices as institutions Strategic complementarities in firm behavior Neighborhood effects in worker behavior Linked domains (Aoki): labor, social, organizational, governance, legal,

political, financial, cognitive, norms, discourse/rhetoric Multiple equilibria – parallel universes

Sociological approach adds value, also more parsimonious?

(Il-)legal practices as institutions “Everybody does it”: accounting fraud, child labor, discrimination,

corruption Endogenous enforcement “Of what use are laws empty of customs?” – Horace

"Everything in life is unusual until you get accustomed to it.”- The Scarecrow in The Marvelous Land of Oz (L. Frank Baum)

Magnitude of Wage Arrears, Firm Data

1991 1992 1993 1994 1995 1996 1997 1998

E(t) 0.073 0.140 0.272 0.552 0.992 1.585 2.239 2.313

E(t t > 0) 1.463 1.970 2.604 2.814 2.833 3.297 3.612 3.817

Unconditional Distribution (t)

t = 0 0.950 0.932 0.899 0.804 0.650 0.519 0.380 0.394

1 month 0.034 0.028 0.022 0.058 0.075 0.065 0.094 0.101

2-3 months 0.013 0.028 0.049 0.098 0.198 0.273 0.311 0.263

4-6 months 0.003 0.012 0.028 0.028 0.057 0.110 0.140 0.154

>6 months 0.000 0.000 0.003 0.012 0.021 0.033 0.074 0.089

N 321 323 325 326 334 337 350 358

Table 2: Characteristics of the Worker Sample

Variable Mean Variable MeanMale 0.473 Hourly Wage Rate (rubles) 12.094Schooling (years) 11.851 (20.033)

(2.524) Family Income (thous.rubles) 0.961Age (years) 39.024 (1.775)

(11.800) IndustryTenure (years) 8.180 Mining 0.023

(9.068) Machine Building 0.109Employee Owns Light and Food 0.049

No shares 0.813 Other Manufacturing 0.102<1% 0.105 Agriculture/Forestry 0.1011% 0.036 Transportation 0.077No information 0.046 Construction 0.071

Occupation Private Services 0.140Managers 0.039 Public Services 0.329Professionals 0.155Technicians 0.177 Public Sector 0.367Clerks 0.072 t (local arrears) 1.612Service Workers 0.096 (1.472)Craft Workers 0.175 Monthly Hours of Work 147.804Operators/Assemblers 0.179 (73.686)Unskilled Workers 0.094 Desire to Switch Jobs 0.383Army 0.013 Quit in Two Years 0.291

Table 3: Characteristics of the Firm Sample

Variable Mean Variable Meant (number of monthly 1.175 Industry

wages overdue) (2.375) Energy & Fuel 0.088

t (local arrears) 1.146 Metallurgy & Chemicals 0.081

(1.321) Machine Building 0.318

Strikes (dummy) 0.019 Wood & Building Materials 0.105

Quit Rate 0.169 Light 0.089

(quits/employment) (0.169) Food 0.135

Legal Penalties (dummy) 0.010 Other 0.060

Union Density (% members) Agriculture 0.123

0-9% 0.086 Type of Location

10-59% 0.095 Moscow and St. Petersburg 0.105

60-79% 0.088 Regional Capital City 0.360

80-89% 0.087 Other City 0.342

90-99% 0.275 Non-City 0.194

100% 0.369 Legal Environment

Firm Fringe Benefits Fraction of cases when 0.098

Training 0.647 managers failed to pay (0.085)

Kindergartens 0.433 assessed fines on time

Housing 0.382 Fraction of cases when 0.216

Training Costs 82.022 arrears were paid off after (0.158)

(days) /100 (92.850) violation was discovered

Previous Empirical Work on Wage

Arrears in Russia

Most studies have examined data on workers:– Desai and Idson (1998)– Earle and Sabirianova (1998)– Gimpelson (1998)– Lehmann, Wadsworth, and Acquisti (1999)

Case studies of firms:– Gimpelson and Lippoldt (1996)– Clarke (1998)

Small sample survey of firms (July 1994):– Alfandari and Schaffer (1996)

Aggregate time-series analysis:– Ivanova and Wyplosz (1998)

Testing Model Assumptions –Wage Exogeneity

Wage arrears are not identical with a reduction in the contractual wage– Uncertainty about timing, extent of eventual payment

– Deferral of compensation => bonding effect

– Workers respond differently to wage arrears and wage cut

– Wage arrears perceived by people as different from a wage cut – more important social issue, according to opinion polls; perceived as legal violation

– Violation of contract, not renegotiation

Estimating a Nonlinear Model of Wage Arrears Interactions

Under the assumption r=eZ, the three symmetric Nash equilibria are

– The punctual payment equilibrium

– The threshold equilibrium

– The late payment equilibrium

0*

1

d

abdcc

2

)2(42

*

2

d

abdcc

2

)2(42

*

3

Testing Model Assumptions –Response of Public Firms to the Local Wage Arrear Environment

Wage arrear function in the public sector

– pjt is the number of unpaid monthly wages of individual pworking in the public sector in district j in period t

– jt is the level of wage arrears in the rest of the firm’s local labor market (district) j in period t

– Zijt is a vector of observable characteristics Gender, age, schooling, tenure, hourly wage rate, family

income, and occupation

Alternative specifications– OLS with district, firm and individual fixed effects

Testable implications– is zero or significantly smaller than in the non-public sector

pjttDjpjtZjtpjt z 0

Table 8: Testing Model Assumptions –Linear Reaction Function, Public Sector

OLS District FE Firm FE Worker

FEPanel At (local arrears) 0.404*** 0.298*** 0.404*** 0.469***

(0.061) (0.076) (0.054) (0.057)Male 0.080 0.071 0.008 …

(0.081) (0.081) (0.134)Schooling (years) 0.007 0.015 -0.000 -0.029

(0.017) (0.016) (0.025) (0.040)Age (years) -0.006 -0.006 0.002 …

(0.004) (0.004) (0.006)Tenure (years) 0.027*** 0.027*** 0.010* 0.006

(0.006) (0.006) (0.006) (0.008)Hourly Wage Rate (rubles) -0.006*** -0.006** -0.007*** -0.008***

(0.002) (0.002) (0.003) (0.003)Family Income -0.024* -0.017 -0.038* -0.039*(thous.rubles) (0.013) (0.014) (0.022) (0.024)R2 overall 0.136 0.150 0.125 0.120Panel Bn

t (local arrears in the non- 0.305*** 0.270*** 0.286*** 0.353***public sector) (0.046) (0.085) (0.043) (0.047)R2 overall 0.132 0.151 0.121 0.092

Searching for New InstrumentsThe Neighborhood Effect in the Defense Industry and Social Security Payments

OLS No FE District FE Firm FE Worker FE

Non-Public Sector 0.894*** 1.008*** 0.975*** 0.839***

(N=12306) (0.088) (0.013) (0.055) (0.051)

Public Sector 0.404*** 0.298*** 0.404*** 0.469***

(N=7010) (0.061) (0.076) (0.054) (0.057)

Defense Industry 0.152 0.002 -0.151 -0.184

(N=1134) (0.104) (0.177) (0.170) (0.180)

Retirement Benefits 0.170*** 0.413*** … 0.379***

(N=5756) (0.054) (0.099) (0.024)

Related Research (2/2)

Institutions– equilibrium strategies in a game (Aoki 2001, 2005)

Contract enforcement– institutional foundation of successful economies (North 1990, Hadfield

2004)– medieval history (Greif, Milgrom, Weingast 1994)– transition (Murrell 1992, Greif & Kandel 1995)

Russian wage arrears– flexible wage adjustment (Layard & Richter 1995: the “neoclassical

economist’s dream labor market”)– empirical regularities with firm data (Alfandari & Schaffer 1996)– empirical regularities with household data (Gimpelson 1998, Lehmann et

al. 1999, Desai & Idson 2000)– within/between firm variation, successful firms with arrears (Earle &

Sabirianova 2002)

“New Institutionalism” in Sociology –critique of economics

Analysis level

– economists “view institutions as epiphenomenal, the mere sum of individual-level properties”

– “neglect of social context and the durability of social institutions” (Powell & DiMaggio)

Rejection of intentionality

– “Institutions include any constraint devised to shape human interaction.” North, 1990

Rejection of functionalism

Reject inattention to cultural/historical context

“New Institutionalism” in Sociology

Higher level of analysis. Durkheim “social facts”

“Spontaneous order”

Focus on thoughts of actors (beliefs)

Concepts of legitimacy, norms (perceived)

Distinguish institutions from mere conventions, “take on a rule-like status”

Difference b/w formal law and social meaning

Emphasis on cultural/historical context)

Reference group: “field,” “habitus” (Bourdieu)

“New Institutionalism” in Sociology – cognitive issues

Unreflective, routine, taken-for-granted behavior

Institutions reproduced because individuals unable to even conceive of appropriate alternatives

“Institutions do not just constrain options; they establish the very criteria by which people discover their preferences… some of the most important sunk costs are cognitive.” (P&D, p. 11)

“Mental models” (Ashforth and Anand, 2003)

Scripts, rituals

Rhetoric, discourse, ideology

Menu of choices defined socially

Possible Factors Raising the Incentives of Managers to Use Wage Arrears

Financial distress and illiquidity– extreme form: no 'live' money– costliness of other methods of adjustments (layoff restrictions)– uncertainty about demand conditions– separations lower than under layoffs or wage cuts– may be a low cost way of preserving employment

Political economy– avoid taxes (signal of inability to pay)– extract subsidies (particularly for large employers)

Poor monitoring of managerial actions– asset stripping, cash flow diversion– GKO (treasury bill) investment – crowding out

Employee ownership arising from privatization– workers extend credit as well as equity to their employers– managers try to force workers to sell their shares

Possible Factors Raising the Incentives of Workers to Tolerate Wage Arrears

Little bargaining power and poor outside options (in some local labor markets) - Lehmann et al. (1998)

Large quasi-rents (high mobility costs and firm-specific human capital)

WA tilts wage-tenure profile, so the labor supply response is uncertain; could even reduce quits and raise hours and effort

Costliness to workers of enforcing wage contracts

Value of job includes fringe benefits, use of company facilities, theft, etc. (Layard and Richter, 1995)

Measurement of Wage Arrears

Firm accounting practice – cumulative monthly wage bills (payrolls) the firm owes to its

workers, without regard to the timing of the overdue payments

The survey question – number of overdue monthly salaries

Both concern the stock, measured in overdue monthly payments

Wage volatility/measurement issues

Implication: wage mismeasured in most studies of Russian labor markets in the 1990s

Data on Russian Employees, Employers, and Wage Arrears

Russian Longitudinal Monitoring Survey (RLMS)– Probability sample of households covering 50 districts (counties)– Panel data, annual 1994-96, 1998, 2000; 10,000 observations each year– Information on labor force activities, wage arrears– Missing industry, other firm characteristics

Improvements to RLMS– Employer identified (1994-2000)– Firm characteristics identified/cleaned, industry coded– Interfirm mobility, firm tenure precisely measured– Added questions

Survey of employers of RLMS employee-respondents– National probability sample of firms– Detailed information on firm ownership, performance, arrears, etc.– Strikes, legal penalties for wage arrears, separations

Result: linked employer-employee data based on a probability sample for all of Russia

Adding Sociology

Giddens (1984): “control of diffuse anxiety is the most generalized motivational origin of human conduct” => stick to routine

Understanding deviance

– Taken-for-grantedness in a normative sense

– “everybody does it”

speeding, illegal downloads, options backdating, discrimination, avoiding nanny taxes, hiring aliens

– Twain: “Everybody complains about the weather but nobody ever does anything about it.”

Other gaps in the economic approach to institutions

Roles of rhetoric and discourse

Difference between formal law and social meaning

March and Olsen (1989): “Practices are routinely chosen – or ignored – on the basis of taken-for-granted norms of behavior. What is taken for granted need not conform with formal laws and regulations.”

What’s on the menu?