transportation infrastructure, industrial productivity and roi · outline introduction literature...

OutlineIntroduction

LiteratureData, Methods and SoftwareTheory, Models and Results

Conclusions

Transportation Infrastructure, IndustrialProductivity and ROI

Jeff EloffOleg A. Smirnov

Peter S. Lindquist

Mid-Continent Transportation Research ForumSeptember 6, 2012

Jeff Eloff Oleg A. Smirnov Peter S. Lindquist Transportation Infrastructure, Industrial Productivity and ROI

OutlineIntroduction


Conclusions

Contents

1 IntroductionWhy public infrastructure?Current Conditions

2 LiteratureCurrent MethodologiesGeographic ScalePublic Capital CreationTypesPublic Capital

3 Data, Methods and SoftwareData

MethodologySoftware

4 Theory, Models and ResultsProfit Margin

Profit Margin Model Results

Aggregate ProductionFunction

Aggregate ProductionFunction Results

Analytical Cost FunctionCost Function Results

5 Conclusions


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Conclusions

Why public infrastructure?Current Conditions

Why Public Infrastructure?

The Importance of Public Infrastructure:

1 Quality of Life

2 Productivity of Business

3 Economic Growth


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US Transportation Conditions

How are we doing?

25th compared to other OECD nations in terms of quality

Traffic Congestion worse than Western Europe

Road fatality rate 60% above OECD average

33,000 Americans in 2010

Airport delays increasing problem


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US Transportation Infrastructure Investment Trends

Investment trends...

Total expenditures have fallen steadily over the last 60 years

From ∼ 5% in the 1960’s to 2.4% of GDP today

Europe invests ∼ 5%

China: 9%


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Investing and Maintaining

US spends more than twice per person as Britain on newconstruction

Spend 25% less on maintainence


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Our Future

Additional $20 billion needed per year to maintain currentsystem!

Census Bureau projects population growth of 40% over thenext 40 years!

In real terms, spending fell an average of 1.6% per year from2003 to 2007.

Need for more methods and approaches to better guideinvestment decision making.


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Current MethodologiesGeographic ScalePublic Capital Creation TypesPublic Capital

Literature

Much work has been done!

Starting with Aschauer [1] in 1989

Many followers – a bit of a methodological debate

Three main classifications of the literature readily emerge:1 Methodology2 Scale3 Way in which Public Capital is measured and defined


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Methodological Divisions

Three major methodological branches:1 Production

Outputs vs inputs, with inclusion of public capital

2 Cost

Dual also take public capital as exogenous, but a determinantof costs

3 VAR

Essentially reduced form models of production, demand andpolicy functionsEasy to mis-specify, fail to identify external shocks to systemNot directly comparable to other models


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Scale Divisions

Many studies vary the scale of analysis:

International

National

Regional

Sectoral

Hypothesized that the magnitude and significance of the results ofpublic capital impacts on productivity vary based upon the level of[geographic] aggregation due to the presence of spatial spilloversbeing captured in the data.


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Public Capital Measures

The way in which the literature classifies public capital variesgreatly depending upon the study

Highway spending

Public Investment

Net Stock of non-military capital

And many more

Common to nearly all is the conversion of the expenditure data(flows) into capital stocks by means of PIM.This necessitates:

1 Gross Investment

2 Initial Benchmark

3 Depreciation Rates


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Our Goal

Aim to uncover which geographic areas, when invested in, willprove most beneficial to industry.

Determine magnitude and extent of benefits to manufacturingindustry that arise from investments in transportationinfrastructure.

Interested in spatial variation of benefits.

Benefits to industry in terms of:

Profit MarginsOutputIndustry Costs


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Public Infrastructure Defined:

Sum of annual State and Local Government expenditures on:

1 Streets

2 Waterports

3 Airports


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DataMethodologySoftware

Data

Two Major Sources:

Annual Survey of Manufactures (ASM) Geographic AreaStatistics

NAICS 31-33 Data from 1997-2010Industry Structure

Government Finance Series

Annual Transportation Expenditures by State and LocalGovernments


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Methodology

We estimate two spatial econometric models:1 Profit Margin Model

Spatial Error Panel Model via KKP’s GMM routine

2 Production Function Model

Elhorst’s Maximum Likelihood Spatial Lag Panel Model

And combine the results of each to analyze Cost...


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Software

Estimation for each:

Profit Margin estimation – Python 2.7

Production Function Model – MATLAB R2011b

Visual Representation – ArcGIS 9.3.1


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Profit MarginAggregate Production FunctionAnalytical Cost Function

Profit Maximizers

We assume that all firms engaging in the industry areprofit-maximizers.

A profit-maximizing firm chooses the level of inputs andoutputs in such a way that maximize economic profit.

This is to say that any given firm partaking in the marketstrives to make decisions in such a way that cause theseparation between total revenue (TR) and total costs (TC) todiverge as far as is possible given current available technology.

Since industrial activity takes place in space we expect thatthere exist some market interactions, agglomerations and thusthat the data contains temporal correlation, spatialdependence and spatial spillovers.


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Profit Margin Model

Therefore, the model takes the form:

πi ,t = α + β1 ¯empi ,t + β2lnPL,i ,t + β3lnPM,i ,t + β4σPFuel,t+

β5PFuel ,t + β6lnKi ,t + β7lnGi ,t + β8lnGi ,t + ui ,t

ui ,t = ρ(IT ⊗WN)ui ,t + εi ,t (1)

εi ,t = (eT ⊗ IN)µi + νt


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Profit Margin Model Variables

where:

πi ,t is defined as 1− totalcosttotalrevenue

¯empi ,t is state i ∈ N’s average firm size

PL,i ,t and PM,i ,t are labor and materials prices

σPFuel ,t is the average annual standard deviation of nationalweekly average fuel prices

PFuel ,t is the national annual average retail gasoline price

Ki ,t is private capital expenditures

Gi ,t represents the sum of transportation capital expenditures

and Gi ,t represents the spatial lag of these transportationexpenditures.


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TABLE 1: Profit Function Estimation ResultsVariable Coefficient Std-Error P-Value Elasticity

α -0.39205 0.13899 0.00493* -1.13401¯firmsize -0.00145 0.00046 0.00159* -0.17971

ln(PL) 0.11827 0.01589 0.00000* 1.59916ln(PM) 0.02461 0.01554 0.11385 0.07380σPFuel

0.00249 0.00325 0.44225 -0.02799¯PFuel -0.05433 0.00765 0.00000* -0.29839

ln(K) -0.01404 0.00369 0.00016* -0.57316ln(G) 0.01879 0.00709 0.00825* 0.41529ln(G ) 0.04915 0.01183 0.00003* 1.12499

ρ 0.42818

R2 0.85708

Breusch-Pagan LM-Statistic 2.77e−10

Chi-Squared Probability 0.99Degrees of Freedom 8


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Own State Public Capital Elasticities


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Neighboring State Investment Benefits


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Production Function Model

We estimate a production function as it allows us to examine therelationship between inputs and outputs:

lnYi ,t = α + ρWlnYi ,t + β1lnGi ,t + β2lnGi ,t + β3lnKi ,t +β4lnPL,i ,t + β5tlnPL,i ,t + β6D06 + εi ,t

εi ,t = µi + νt (2)


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Table 2: Production Function Estimation ResultsVariable Coefficient P-Value

α 0.04264 0.00000*lnG 0.20765 0.00000*lnG 0.46304 0.00000*lnK 0.05184 0.00000*

lnPL 0.77131 0.00000*tlnPL -0.00033 0.25440

D06 0.03464 0.07511ρ 0.45398 0.00000*

R2 .9868

Breusch-Pagan LM-Statistic 1.8610Chi-Squared Probability 0.9320

Degrees of Freedom 6


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Figure : Theme barsJeff Eloff Oleg A. Smirnov Peter S. Lindquist Transportation Infrastructure, Industrial Productivity and ROI

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Figure : Theme AntibesJeff Eloff Oleg A. Smirnov Peter S. Lindquist Transportation Infrastructure, Industrial Productivity and ROI

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Cost Function

Traditionally examined in a [dual] cost based framework

Substituting the profit margin and production functions intothis expression yields:

πi,t = 1− TCi,t

Yi,t

TCi,t = Yi,t − Yi,t × πi,t


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Cost Function Results

Assume 1 percent increase in own state public capital

Y ↑ 0.20765 (Table 2)π ↑ 0.01879 (Table 1)

TC = -0.20374


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Neighboring Public Capital on Cost

Assume 1 percent increase to Neighboring State PublicCapital:

Y ↑ 0.46304 (Table 2)π ↑ 0.04915 (Table 1)

TC = −0.44


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Cost Function

An Increase in G or G benefits both Output and ProfitMargins

G ≈ Twice the Effect of Own State Expenditures

Neighboring Capital is ‘free’

Out-Of-State Users Do Not Pay Taxes for Neighboring StateExpenditures


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Conclusions

Public Capital Significant

Reduces MFG Production Costs

Increases Profit Margins

Significant Spatial Spillovers

Appear to be increasing over time


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Sources

[1]Aschauer, D. (1989). ”Is public expenditure productive?”.Journal of Monetary Economics, Vol. 23, No. 2, pp. 177–200.

[2]Treasury, Dept of (2010). Economic Analysis of InfrastructureInvestment.

[3]Baird, Brian A. (2005). Public Infrastructure and EconomicProductivity A Transportation-Focused Review. TransportationResearch Record, 1932, 54–60.

[4]Pereira, A. M., & Andraz, J. M. (2010). On the economiceffects of public infrastructure investment: A survey of theinternational evidence. College of William and Mary: WorkingPaper Number 108.


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Questions? Comments?


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