Original Research General Interest Articles

Do State Corporate TaxIncentives Create Jobs?Quasi-experimental Evidencefrom the EntertainmentIndustry

Michael Thom1

AbstractPolicy makers allocate billions of dollars each year to tax incentives that increasingly favor creativeindustries. This study scrutinizes that approach by examining motion picture incentive programsused in over thirty states to encourage film and television production. It uses a quasi-experimentalstrategy to determine whether those programs have contributed to employment growth. Resultsmostly show no statistically significant effects. Results also indicate that domestic employment isunaffected by competing incentives offered outside the United States. These findings are robust toseveral alternative models and should lead policy makers to question the wisdom of targetedincentives conferred on creative industries.

Keywordseconomic development, tax, tax incentive

For over a century, state and local policy mak-

ers have sought to encourage economic devel-

opment by offering incentives that target

specific firms and industries. But targeted

incentives have only recently drawn consider-

able scrutiny, thanks in part to their escalating

cost. For example, Tesla agreed in 2014 to build

a factory in Nevada after officials there offered

tax and other incentives valued at US$1.3

billion. Foxconn decided in 2017 to locate new

facilities in Wisconsin in response to incentives

valued at between US$3 billion and US$4.5

billion. Several governments later competed

over Amazon’s HQ2 project with incentive

packages worth as much as US$8.5 billion.

Whether through so-called megadeals or

other programs that attract less notice, the use

of targeted incentives shows no sign of abating.

Sixty-eight percent of state and local govern-

ments offered them in 1999; by 2009, it was

95 percent (Florida 2018). The roots of that

growth lay in the political environment. Policy

makers use incentives to signal proactiveness

on the economy, and targeting a specific firm

or industry brings greater visibility to their

1 Price School of Public Policy, University of Southern

California, Los Angeles, CA, USA

Corresponding Author:

Michael Thom, Price School of Public Policy, University

of Southern California, 650 Childs Way, MC 0626,

Los Angeles, CA 90089, USA.

Email: mdthom@usc.edu

State and Local Government Review1-12ª The Author(s) 2019Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/0160323X19877232journals.sagepub.com/home/slg

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efforts than offering nonparticularized incen-

tives. If the target ultimately locates in an

area that proposed incentives, policy makers

benefit by taking credit. If it settles else-

where, policy makers may still benefit by

taking credit for making an attempt to create

jobs, deflecting any blame to problems

beyond their control.

Of course, policy makers do not act in a

vacuum. Offered a choice between a policy

maker who offers incentives and one who

does not, voters prefer the former even if

both attract the same development (Jensen

and Malesky 2018). For their part, busi-

nesses develop rent-seeking relationships

with policy makers to protect incentives

against electoral turnover—a quid pro quo

that metastasizes to other rent-seeking

arrangements (Coyne, Sobel, and Dove

2010; McChesney 1997).

If there’s a voice of caution in the milieu, it

comes from those who assess targeted incen-

tives. Indeed, studies commonly find that they

do not yield promised benefits (e.g., Peters and

Fisher 2004). But evaluative research has failed

to keep pace with targeted incentives’ prolifera-

tion, making it difficult for policy makers to

judge whether or not they’re a prudent use of

resources.

This study investigates the employment

impact of motion picture incentive (MPI)

programs, a combination of corporate tax

incentives and other services made available

by over thirty state governments to encour-

age film and television production. MPI pro-

grams are one component of a broader

strategy across those governments to diver-

sify economies by incenting a creative indus-

try believed to yield stable, high-wage jobs.

To that end, policy makers in some states

have approved higher tax expenditures for

MPI programs than many prominent mega-

deals. As such, they are a relevant case from

which to draw implications about the effi-

cacy of targeting an industry with exclusive

incentives—in this case, a creative industry

with a high degree of mobility and, in theory,

high sensitivity to those incentives.

Targeted Economic DevelopmentIncentives in Context

The inclination toward targeted economic

development approaches in the United States

has roots in the Great Depression. During that

period, policy makers in southern states

enacted bond programs that subsidized facto-

ries and other facilities, thereby lowering firms’

effective capital costs. That bond-supported

infrastructure was publicly owned and exempt

from property taxation yielded further cost

advantages (LeRoy 2005). Many observers

believed this tactic successfully enticed labor

and capital from northern states, where policy

makers responded with retaliatory incentives.

Competition accelerated through the 1970s and

1980s and became more global in scope (Jenn

and Nourzad 1996). Incentives evolved toward

further particularization as policy makers—

seeking ever-narrowing competitive advan-

tages—began to target specific firms and indus-

tries as well as locations (e.g., downtown cores,

enterprise zones, and brownfield sites) and

events (e.g., the Summer Olympics).

The accumulated findings of an extensive

literature on targeted incentives converge

toward a single conclusion about their efficacy.

In short, studies suggest policy makers should

avoid the practice altogether, especially with

incentives that carry tax expenditures, because

they fail to stimulate commensurate economic

gains (e.g., Fox and Murray 2004; Hicks and

LaFaive 2011; Kolko and Neumark 2010; Neu-

mark and Kolko 2010; Patrick 2014; Reese

2014). In instances where gains materialize,

they may be short term (e.g., O’Keefe 2004;

Wassmer 1994; see also Hamersma 2008).

Lackluster outcomes have many causes.

Most state and local business tax frameworks

are not appreciably different, rendering any sin-

gle incentive unable to rouse substantial firm

relocation or expansion (Wasylenko 1997).

Furthermore, taxes for many industries are not

a primary operating cost. Among manufactur-

ers, for example, taxes compose around 1 per-

cent of input costs compared to over 21

percent for labor (Keynon, Langley, and Paquin

2012). Marginal tax reductions offered in one

2 State and Local Government Review XX(X)

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area may thus fail to compensate for other costs

that may be higher in the same area. Competi-

tive targeting can also create a zero-sum game

in which one area’s “win” comes at the expense

of another’s loss (Chirinko and Wilson 2008;

Wilson 2009).

Targeting nevertheless endures, and the tar-

gets have evolved. Policy makers in many state

and local governments have oriented their eco-

nomic development strategies toward growing

the “creative class” and building “creative

cities” into a “creative economy” (Florida

2002; Howkins 2001; Scott 2000). The strategy

is vested in a belief that creative, knowledge-

intensive industries—that is, sectors in which

intellectual property is the output—produce

stable, high-wage jobs that serve as a growth

driver and a buffer against economic shocks.

The argument is especially attractive in areas

where policy makers have struggled to revive

economies decimated by losses in manufactur-

ing and other heavy industries.

But the approach engenders an intractable

Catch-22. For all the benefits of a creative

economy, there are drawbacks, among them

gentrification, rising housing costs, and higher

inequality. Compared to traditional industry

clusters, the market for creative labor and cap-

ital is more global and competitive (Florida

2005). And relative to other industries (e.g.,

agriculture, manufacturing, and natural

resource extraction), those built on intellectual

property are less tethered to any one location.

Incentives can create jobs more rapidly, but

those jobs can just as rapidly leave.

Chasing Hollywood

Incentives conferred on the motion picture

industry, including film, television, and com-

mercial production, have been a crucial ele-

ment of strategies focused on creative

industry development (Christopherson 2008).

Most states and some local governments have

made relatively low-cost support services, such

as location assistance coordinated by a

taxpayer-funded film office, available to the

industry for decades. But in the late-1990s and

early-2000s, policy makers in many states

expanded those services and added corporate

tax incentives that were not available to other

sectors (Christopherson and Rightor 2010).

These MPI programs eventually spread to

forty-four states, carried by rising unemploy-

ment and domestic competition (Leiser 2017;

Thom and An 2017).

Although the number of MPI programs has

declined, investment has not. In 2017, accord-

ing to state government reports, over thirty

states granted the industry a combined

US$1.7 billion in corporate income tax expen-

ditures, not including the value of other pro-

gram services. About 77 percent was

concentrated in five high-expenditure states

(New York, Louisiana, Georgia, Connecticut,

and Massachusetts) that represented only 58

percent of expenditures five years earlier.

Cumulative spending in these states rival those

for prominent economic development mega-

deals (see Table 1).

Each high-expenditure state’s MPI program

has common features, including location assis-

tance, advertising, and preferential regulatory

treatment. Some include sales and transient

occupancy tax waivers and incentives for

building production-related infrastructure.

States differentiate themselves with corporate

income tax credits that vary from 10 to 40 per-

cent of production spending, with a typical

range of 25–30 percent. Specific information

on each state’s program is available in

Supplement Table S1.

Because tax credit rates are high, tax credit

values exceed most productions’ state corpo-

rate income tax liability. To resolve the differ-

ence, a state designates its credit as either

refundable (i.e., the state issues a cash refund

for the difference between the credit’s value

and the production’s tax liability) or transfer-

rable (i.e., the state allows the production

to transfer the excess credit to other projects

and/or allows the production to sell the

excess credit to a third party). Among high-

expenditure states, two have refundable tax

credits (New York and Louisiana), two have

transferrable tax credits (Georgia and Connecti-

cut), and one allows each production a choice

(Massachusetts). Regardless of tax credit

Thom 3

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structure, by reducing effective production

costs, MPI programs theoretically encourage

hiring activity that would not have transpired

otherwise, thus encouraging each state’s crea-

tive economy.

Research Design

Scope

The typical method for evaluating MPI pro-

grams is a panel study that includes all states

(e.g., Swenson 2017; Thom 2018). While stud-

ies adopting that frame have yielded valuable

insights, their results have three limitations.

First, they do not consistently account for

incentive differences across the states. Second,

they rarely produce state-specific findings,

leaving unresolved the question of whether

MPI programs are consistently poor performers

or if middling impacts result instead from neg-

ative effects in some states canceling out posi-

tive effects elsewhere. Third, they do not

address how incentives offered outside the

United States affect domestic employment.

This study aims to advance understanding of

MPI programs, and incentives that target crea-

tive industries more broadly, by addressing

those limitations. It focuses on the high-

expenditure states described in Table 1. Over

three-quarters of recent tax expenditures

occurred in those five states, and if employment

increases have not emerged there, then states

with markedly lower investment can scarcely

hope to achieve a better outcome. Moreover,

thanks to billions of dollars in investment, the

likelihood of MPI program termination in

high-expenditure states is low, suggesting these

programs will remain in effect (Thom and An

2017). Estimating a separate model for each

state also produces a more nuanced view of

program impacts: It is likely that, despite

implementing a similar incentive scheme, each

state has experienced a different outcome.

Outcome Variable

Scrutinizing a tax incentive’s employment

impact requires careful attention. Analyses

funded by the motion picture industry and some

from economic development agencies tend to

credit tax incentives for job creation and blame

a lack of incentives for job losses. But common

sense and data from the U.S. Bureau of Labor

Statistics suggest another reality. To wit, each

high-expenditure state reported hundreds, if not

thousands, of motion picture industry jobs

before MPI program implementation and the

number of jobs varied from year to year. But

both conditions were also present after incen-

tives were available. This study’s objective is

thus to determine the degree to which those

incentives, rather than confounding factors,

drove employment changes.

Consistent with prior research, the outcome

variable is the annual percentage-point change

Table 1. Cumulative and Projected Motion Picture Incentive Program Tax Expenditures amongHigh-expenditure States.

State Year Enacted Cumulative Expenditure Projected 20-year Expenditure

New York 2004 $4.65 billion $8.74 billionLouisiana 2002 $2.29 billion $3.36 billionGeorgia 2005 $1.54 billion $4.58 billionConnecticut 2006 $1.00 billion $1.65 billionMassachusetts 2005 $0.50 billion $1.05 billion

Source: New York: Empire State Development Quarterly Report and Department of Taxation and Finance Annual Report onNew York State Tax Expenditures; Louisiana: Office of Entertainment Industry Development; Georgia: Department of Auditsand Accounts Tax Expenditure Report; Connecticut: Department of Economic and Community Development AnnualReports; and Massachusetts: Executive Office for Administration and Finance Tax Expenditure Budgets.Note: Cumulative expenditures are reported through 2017 and in constant 2017 dollars, adjusted using the Consumer PriceIndex. Projected expenditures assume the state’s most recent annual tax expenditure will remain fixed for the balance of aprogram length of twenty years.

4 State and Local Government Review XX(X)

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in each state’s motion picture industry employ-

ment. The variable is derived from Quarterly

Census of Economics and Wages (QCEW) data

on North American Industry Classification Sys-

tem Code 512110, “Motion Picture and Video

Production.” This category includes employ-

ment tied to the production of “motion pictures,

videos, television programs, or television

commercials.” Given the emphasis on job cre-

ation, assessing employment is advantageous

to the raw number of incented television or film

productions. Evaluating annual employment

changes instead of annual employment totals

also avoids one source of endogeneity that

states with high employment established an

MPI program (perhaps as a result of industry

lobbying) and subsequently continued to report

high employment.

Explanatory Variables

Explanatory variables fall into two categories:

internal factors and competitive factors. Inter-

nal factors comprise two characteristics spe-

cific to each state. First and most important,

all models incorporate changes to tax expendi-

tures issued under each MPI program as

reported by each state. If targeted tax incen-

tives motivate positive employment outcomes,

then an increase in tax expenditures should

correspond with an increase in employment.

Second, given the relationship between labor

costs and employment in any industry, all

models incorporate changes in average Motion

Picture and Video Production wages per

employee reported in the QCEW.1 Each vari-

able is measured as the annual percentage-

point change in constant-dollar figures.

Competitive factors comprise a set of vari-

ables that reflect the dynamic tax incentive

environment. Because any of the high-

expenditure states may lose or gain employ-

ment as a result of changes to competing

governments’ tax incentives, each state’s

annual employment change is modeled as a

function of both their tax expenditure and tax

expenditures in competing areas. All models

control for tax expenditures in each of the other

high-expenditure states; all other states

combined; and Canada, inclusive of Canadian

federal incentives and provincial incentives

offered in British Columbia and Ontario,

adjusted to their then-current U.S. dollar

equivalents. Canada’s inclusion is essential; it

has long been invoked as a competitor for

domestic motion picture industry employ-

ment. The industry, its labor unions, and

economic development officials regularly

use the presence of Canadian incentives,

and those available in British Columbia

and Ontario in particular, as justification

to expand domestic incentives. Failing to

do so, they argue, will result in “runaway

production”—a flight of jobs from the United

States to Canada. Each variable is measured

as the annual percentage-point change in

constant-dollar figures.

Controls

All models include two control variables: the

national change in Motion Picture and Video

Production employment (excluding the state

in question) and the change in each state’s over-

all private-sector labor force (excluding Motion

Picture and Video Production employment).

Each variable is measured as the annual

percentage-point change in annual employment

totals reported in the QCEW. Descriptive

statistics for all variables are available in

Supplement Table S2.

Empirical Strategy

This study uses an interrupted time series anal-

ysis (ITSA). Generally speaking, ITSA models

separate longitudinal data into observations

drawn before and after a discrete intervention

and estimate the intervention’s effect on postin-

tervention observations. Since ITSA models

are comparable to randomized experimental

designs (St. Clair, Cook, and Hallberg 2014),

they are widely used in health and behavioral

economics research and also have broad reach

in policy analysis, where experimental designs

are often unworkable (e.g., Bonham et al. 1992;

Muller 2004; Sutherland et al. 2017; see also

Cook 2014).

Thom 5

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As applied here, MPI program implementa-

tion is the intervention. Data from each state are

separated into a preintervention phase (i.e., data

from years preceding implementation) and

postintervention phase (i.e., data from years

following implementation; see Table 2). To

produce symmetric phases that avoid time bias,

pre- and postintervention phases are of equal

length. For example, New York enacted its

Film Production Tax Credit in 2004, but appli-

cations were not accepted until the latter half of

2004. Since 2005 was the first year in which

any employment effects were likely measur-

able, New York’s postintervention phase is

2005–2017 or thirteen years in length. Its prein-

tervention phase is also thirteen years in length,

1992–2004. The only exception is Louisiana.

Its preintervention phase should be 1987–

2001, but the QCEW does not report industry-

and state-specific data from 1987–1990. Con-

sequently, Louisiana’s preintervention phase

is truncated by four years.

While many ITSA iterations exist, this study

uses the model developed by Linden (2015),

which utilizes a generalized least-squares

regression that assumes a first-order autore-

gressive error structure but no heteroscedasti-

city. Initial diagnostic tests supported both

assumptions. In addition to coefficients for

explanatory and control variables, the model

estimates additional parameters of interest: the

annual motion picture industry employment

change prior to MPI program implementation

(b1), the program’s immediate employment

impact (b2), and its impact over time (b3).

ITSA offers certain advantages over alterna-

tive empirical strategies. Since the model uses

each state’s preintervention phase as a counter-

factual, it sidesteps the challenges inherent to

other methods (e.g., regression discontinuity

and difference-in-differences designs) that

require identifying one or more control states

without incentives to benchmark against states

that have them. Given the dearth of control can-

didates—only six states never enacted an MPI

program—and the distinctive nature of each

state’s motion picture industry—from the size

of the labor force to the state’s incentive timing,

tax expenditures, and climate and geographic

features that shape production location

choice—those methods are inadvisable. Addi-

tional information on this study’s empirical

strategy appears in Text 1 Supplement.

Findings

Empirical results are reported in Table 3. Each

model is a strong fit of the underlying data.

Additional goodness-of-fit information is avail-

able in Figure 1 Supplement. Turning first to

the question of how MPI programs impacted

employment in the five high-expenditure states,

the results show the answer is “not much.” This

study’s empirical strategy sheds light on three

outcomes of interest: b2, which represents the

immediate, permanent program impact; b3,

which represents the subsequent, annual effect

that may add or subtract from b2; and a separate

coefficient for tax expenditures.

The results show a statistically significant,

immediate impact in one state: Connecticut,

Table 2. Pre- and Postintervention Phases for Time Series Analysis.

State Incentive Enactment and Availability Preintervention Phase Postintervention Phase

New York Enacted 2004, available 2005 1992–2004 2005–2017Louisiana Enacted mid-2002, available 2002 1991–2001 2002–2017Georgia Enacted 2005, available 2006 1994–2005 2006–2017Connecticut Enacted 2006, available late-2006 1996–2006 2007–2017Massachusetts Enacted early 2006, available 2006 1994–2005 2006–2017

Source: Enactment and availability timing based on information reported by each state government.Note: For all states but Louisiana, the number of years in the preintervention phase is equal to the number of years in thepostintervention phase. Louisiana’s preintervention phase is truncated by five years because state- and industry-level data areunavailable from the Quarterly Census of Economics and Wages from 1987 through 1991.

6 State and Local Government Review XX(X)

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where the coefficient is large (b2 ¼ 90.803 or

about 91 percentage points). Two points of con-

text are important when interpreting this find-

ing. First, the increase is attributable to

nontax components of the state’s MPI program.

The tax expenditure coefficient is not statisti-

cally significant, indicating that larger expendi-

tures did not contribute to employment gains in

Connecticut nor did smaller expenditures con-

tribute to employment losses. Second, at about

500 employees, Connecticut’s motion picture

industry labor force was small when the state’s

MPI program was implemented. That skews the

proportionality of an otherwise small improve-

ment in total employment. A relatively slight

increase of fifty employees would equate to a

10 percentage point increase in Connecticut,

for instance, but only a 3 percentage point

increase in Massachusetts, where the workforce

is larger.

The results show a statistically significant

program effect over time in one state, Louisiana

(b3 ¼ 10.878 or about 11 percentage points

annually). Unlike Connecticut, the Louisiana

model suggests employment was responsive

to changes in corporate tax incentives (b ¼1.108, indicating each 1 percentage point

increase in tax expenditures corresponded with

a 1.108 percentage point increase in employ-

ment). These findings should also be inter-

preted with caution. Due to limited data

availability, the Louisiana model was estimated

using unbalanced pre- and postintervention

phases; if the model is reestimated with

balanced phases, both coefficients lose statisti-

cal significance.

The influence of corporate tax expenditures

on employment elsewhere was mixed. Like

Connecticut, expenditures in New York had

no statistically significant relationship with

employment. Although statistically significant,

coefficients for Georgia (b ¼ 0.507) and Mas-

sachusetts (b ¼ 0.144) indicate that employ-

ment there was inelastic to tax expenditures—

a 1 percentage point change in tax expenditures

did not propel a comparable change in employ-

ment. There is no clear pattern between these

findings and whether the tax credit was refund-

able (New York), transferrable (Connecticut

and Georgia), or both (Massachusetts), but—

consistent with Thom (2018)—two of the three

states with transferrable credits showed at least

some employment sensitivity. It may be that

because it is more difficult to monetize trans-

ferrable credits, productions that wish to realize

those credits’ full value must return to the issu-

ing state and engage in further economic activ-

ity. That, in turn, may drive additional—if

trivial—employment gains.

The results offer evidence of interstate com-

petition, but all coefficients suggest inelastic

responses. For example, at the national level,

employment in Louisiana decreased as tax

expenditures rose in New York (b ¼ �0.444),

perhaps because New York’s program was

enacted just two years after Louisiana’s and

quickly grew to become the largest. At a

regional level, employment in Massachusetts

increased as tax expenditures rose in contigu-

ous New York (b ¼ 0.209) but decreased as tax

expenditures rose in contiguous Connecticut

(b¼ �0.166). But in Connecticut, employment

fell by an almost identical degree (b ¼ �0.170)

as tax expenditures rose in Massachusetts. That

finding implies minor labor competition

between Connecticut and Massachusetts, prox-

imate states with other shared characteristics

(e.g., climate and a coastal border).

Three additional findings are worth under-

scoring. First, the results suggest a trade-off

between employment gains and wage gains in

two states (see also Note 1). Each 1 percentage

point wage increase in Louisiana was associ-

ated with a 0.780 percentage point decrease in

employment. Results for New York point to a

similar trade-off. While the industry’s highly

transitory nature makes it likely wage and

employment changes occur in close time

proximity, both of these findings were robust

to lagging wages by one year.

Second, the models do not indicate any

domestic employment sensitivity to Canadian

tax incentives. The associated variable merged

Canadian federal incentives with those offered

in two provinces, but the finding was robust

to estimating each model to control for federal

and provincial incentives separately. Null

effects were mostly robust to expanding the

8 State and Local Government Review XX(X)

Deadlin

e

model to include competing incentives in

California and in the United Kingdom.2

Third, employment changes in four states

showed no association with motion picture

employment changes nationally. The sole

exception is New York, which had the largest

preexisting motion picture industry labor force.

It is to be expected that as the industry’s

employment rose and fell nationwide, the effect

would be mirrored in New York regardless of

the presence or absence of an MPI program.

Finally, the findings reported in Table 3

were robust to several alternative model speci-

fications. These are described and reported in

Text 2 Supplement, Table 3 Supplement, Text

3 Supplement, Table 4 Supplement, Text 4

Supplement, and Table 5 Supplement.

Conclusions

State and local governments in the United

States allocate tens of billions of dollars annu-

ally to economic development incentives that

target specific firms and industries. In recent

years, policy makers have shown a preference

for conferring corporate tax incentives and

other supports on the creative sector in the

hopes of creating stable, high-wage jobs. That

trend has occurred despite academic research

that questions whether targeting is an effective

strategy.

This study contributes to that literature by

reporting the impact of MPI programs, a bundle

of corporate tax incentives and other services

for the motion picture industry. Its objective

was to determine whether MPI programs

impacted employment in the five states with the

highest cumulative tax expenditures. Instead of

a panel analysis, this study utilized a quasi-

experimental, interrupted time series model.

Results showed that in most cases, MPI

programs had no statistically significant

employment impact. Findings that achieved

statistical significance nevertheless failed to

show practical significance. These uninspir-

ing employment effects reiterate those in

other econometric (e.g., Swenson 2017;

Thom 2018) and state-specific MPI program

assessments (e.g., Adkisson 2013; Gross and

Stogel 2010; Murray and Bruce 2017). And

they further reinforce the existing literature’s

general conclusion that, as an economic

development strategy, targeted incentive pro-

grams that carry large tax expenditures fail to

encourage meaningful job creation.

This study’s results should encourage policy

makers to exercise caution before pursuing tar-

geted economic development programs, espe-

cially those that incent creative industries.

When the output is intellectual property, pro-

duction can occur anywhere, and the jobs cre-

ated as a result of incentives—if any—are far

from long term. In a competitive market, the

only hope to retain those jobs is to increase tax

and other incentives, the very same “race to the

top” observed when state and local govern-

ments try to outbid each other for the latest pur-

ported engine of economic growth (e.g., Tesla,

Foxconn, Amazon, or a professional sports

franchise). That inevitably creates a bubble in

which policy makers have overinvested in a

program relative to the program’s ability to

yield a return on investment (Maor 2014).

This study has some limitations. It does not

provide a direct assessment of MPI cost-

effectiveness, yet a separate analysis may not

be required. Comparing the tax expenditures

reported in Table 1 against the scarcity of

employment gains attributable to that invest-

ment suggests MPI programs are anything but

a prudent use of taxpayer dollars. This study also

does not thoroughly investigate the relationship

between MPI programs and industry wages.

However, some evidence points toward a

trade-off between employment gains and wage

gains, particularly in New York and Louisiana.

This study also highlights avenues of future

research. The employment dynamics consid-

ered here state level, not local. Whether MPI

programs facilitate job creation at the city or

county level remains understudied, and so does

whether those gains—if any—are real increases

or merely a relocation of jobs from one locality

to another. The motion picture industry also has

specific characteristics, such as relatively short

production time frames, that differentiate it

from other creative industries that have a higher

likelihood of remaining in one location for

Thom 9

Deadlin

e

extended periods, including publishing, fash-

ion, and architecture. Whether incentives tar-

geting those or other less nomadic creative

industries have similar effects to those targeting

the motion picture industry warrants further

scrutiny. To that end, researchers should

explore the use of ITSA models and other

quasi-experimental research designs that seek

to isolate program impacts from confounding

factors, an ever-present challenge in economic

development analysis.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest

with respect to the research, authorship, and/or pub-

lication of this article.

Funding

The author disclosed receipt of the following finan-

cial support for the research, authorship, and/or pub-

lication of this article: Koch Foundation.

ORCID iD

Michael Thom https://orcid.org/0000-0002-8266-

9917

Supplemental Material

Supplemental material for this article is available

online.

Notes

1. Although one might expect affinity between

wage and tax expenditure changes, correlation

statistics suggest otherwise. In New York, the

correlation between wage changes and tax expen-

diture changes was .10; in Georgia, .16; in

Louisiana, .50; in Connecticut, .46; and in Massa-

chusetts, .03.

2. A statistically significant effect appeared in two

states: New York, which gained employment as

California’s tax expenditures increased (b ¼ 0.

143) but lost as they increased in the United King-

dom (b ¼ �0.740); and Connecticut, which lost

employment as tax expenditures increased in both

areas (b ¼ �0.205 and �1.406, respectively).

Full results available from the author upon

request.

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Author Biography

Michael Thom is an associate professor at the

University of Southern California’s Price School of

Public Policy. This is his third article in State and

Local Government Review. His other research has

appeared in Public Administration Review and the

American Review of Public Administration.

12 State and Local Government Review XX(X)

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