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The Political Timing of Tax Policy: Evidence from U.S. States

  • Andrew C. Chang ORCID logo EMAIL logo , Linda R. Cohen , Amihai Glazer and Urbashee Paul
Published/Copyright: May 22, 2025
The B.E. Journal of Economic Analysis & Policy
From the journal The B.E. Journal of Economic Analysis & Policy Volume 25 Issue 3

Abstract

We examine whether politicians avoid tax increases in election years. Using a pre-analysis plan and new data from U.S. states that distinguish between when taxes are legislated and when they come into force, we find that in an election year enacted gasoline and corporate income tax increases are less likely and implemented tax changes are smaller. We do not find evidence that these election-year effects depend on balanced budget rules, term limits, the state’s liberal-conservative ideological bent, demographics, macroeconomic conditions, or on changes in overall legislative output in election years. These effects are stronger for gasoline taxes, consistent with a legislative response to the high political salience of gasoline taxes.

Keywords: corporate income taxes; electoral cycle; gasoline tax; pre-analysis plan; political budget cycle; tax salience
JEL Classification: D72; D78; H24; H71; K34; P16
Corresponding author: Andrew C. Chang, Division of Research and Statistics, Board of Governors of the Federal Reserve System, Washington DC, USA, E-mail: , https://sites.google.com/site/andrewchristopherchang

Funding source: University of California – Irvine

Award Identifier / Grant number: NA

Acknowledgments

We thank Zahra Aghababa and Jiwon Son for superb research assistance. We thank Sarena F. Goodman, Christopher Karlsten, Dalton Ruh, two anonymous referees, and seminar participants at KTH and the NTAs for helpful comments. We thank Ellen Augustiniak for aid in interpreting tax laws. We thank Yilin Hou for providing data on state balanced budget rules. The views and opinions expressed here are ours and are not necessarily those of the Board of Governors of the Federal Reserve System. This paper was previously circulated as “Politicians Avoid Tax Increases Around Elections” (Chang et al. 2021). This paper was supported by the Program in Corporate Welfare at the University of California – Irvine.

  1. Competing interests: All authors declare no financial competing interests. No IRB approvals were needed.

Appendices Appendix A: Figures and Tables

Figure A.1: Implemented and enacted gas taxes are smallest in an election year. Description: Average marginal effects from models that interact measures of voter attentiveness with our electoral cycle indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: Relative to (1a) through (2d), the estimates are more imprecise, but the point estimates still suggest implemented and enacted gas taxes are smallest in an election year. We find no similar electoral effect for the CIT.
Figure A.1:

Implemented and enacted gas taxes are smallest in an election year. Description: Average marginal effects from models that interact measures of voter attentiveness with our electoral cycle indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: Relative to (1a) through (2d), the estimates are more imprecise, but the point estimates still suggest implemented and enacted gas taxes are smallest in an election year. We find no similar electoral effect for the CIT.

Figure A.2: Gubernatorial election effect is not dependent on voter attentiveness. Description: Average marginal effects from models with our electoral indicators interacted with two proxies for voter attentiveness. The top panel shows results for the gubernatorial indicator interaction with average education level and the bottom panel shows the interaction with average newspaper circulation. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: We find that the effect of gubernatorial elections, or lack thereof, on tax enactment or implementation does not depend on a state’s voter attentiveness.
Figure A.2:

Gubernatorial election effect is not dependent on voter attentiveness. Description: Average marginal effects from models with our electoral indicators interacted with two proxies for voter attentiveness. The top panel shows results for the gubernatorial indicator interaction with average education level and the bottom panel shows the interaction with average newspaper circulation. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: We find that the effect of gubernatorial elections, or lack thereof, on tax enactment or implementation does not depend on a state’s voter attentiveness.

Figure A.3: Taxes do not depend on voter attentiveness more than two years after an election. Description: Average marginal effects from models with our electoral indicators interacted with two proxies for voter attentiveness. The top panel shows results for the interaction for being in years 2 or 3 after a gubernatorial election with average education level and the bottom panel shows the interaction with average newspaper circulation. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: We do not find that tax enactment or implementation at least two years after a gubernatorial election depends on a state’s voter attentiveness.
Figure A.3:

Taxes do not depend on voter attentiveness more than two years after an election. Description: Average marginal effects from models with our electoral indicators interacted with two proxies for voter attentiveness. The top panel shows results for the interaction for being in years 2 or 3 after a gubernatorial election with average education level and the bottom panel shows the interaction with average newspaper circulation. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1900 (50); 1350 (50). Interpretation: We do not find that tax enactment or implementation at least two years after a gubernatorial election depends on a state’s voter attentiveness.

Figure A.4: Gas taxes and the CIT are least likely to be enacted in an election year. Description: Average marginal effects from models that interact measures of U.S. macroeconomic conditions with our electoral indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: The results from this model are similar to those from (1a) through (2d). Implemented gas taxes are smallest in an election year, but we find no similar electoral effect for the CIT. Both the gas tax and the CIT are least likely to be enacted in an election year and are most likely to be enacted in the year after the election.
Figure A.4:

Gas taxes and the CIT are least likely to be enacted in an election year. Description: Average marginal effects from models that interact measures of U.S. macroeconomic conditions with our electoral indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: The results from this model are similar to those from (1a) through (2d). Implemented gas taxes are smallest in an election year, but we find no similar electoral effect for the CIT. Both the gas tax and the CIT are least likely to be enacted in an election year and are most likely to be enacted in the year after the election.

Figure A.5: Election year effect does not depend on U.S. macroeconomic conditions. Description: Average marginal effects from models that interact our electoral indicators with two measures of U.S. macroeconomic conditions, oil prices, and corporate profits, on tax implementation and enactment. The top panel shows the gubernatorial election indicator interacted with oil prices and the bottom panel shows the interaction with corporate profits. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: The effect of elections on tax implementation or enactment at the state level does not depend on U.S. macroeconomic conditions.
Figure A.5:

Election year effect does not depend on U.S. macroeconomic conditions. Description: Average marginal effects from models that interact our electoral indicators with two measures of U.S. macroeconomic conditions, oil prices, and corporate profits, on tax implementation and enactment. The top panel shows the gubernatorial election indicator interacted with oil prices and the bottom panel shows the interaction with corporate profits. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: The effect of elections on tax implementation or enactment at the state level does not depend on U.S. macroeconomic conditions.

Figure A.6: Tax implementation two or more years after an election may depend on U.S. macroeconomic conditions, but enactment does not. Description: Average marginal effects from models that interact our electoral indicators with two measures of U.S. macroeconomic conditions, oil prices, and corporate profits, on tax implementation and enactment. The top panel shows the interaction for being in years 2 or 3 after a gubernatorial election interacted with oil prices. The bottom panel shows the interaction with corporate profits. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: At least two years after a state gubernatorial election, tax implementation is more likely when oil prices are higher. Tax enactment does not depend on U.S. macroeconomic conditions.
Figure A.6:

Tax implementation two or more years after an election may depend on U.S. macroeconomic conditions, but enactment does not. Description: Average marginal effects from models that interact our electoral indicators with two measures of U.S. macroeconomic conditions, oil prices, and corporate profits, on tax implementation and enactment. The top panel shows the interaction for being in years 2 or 3 after a gubernatorial election interacted with oil prices. The bottom panel shows the interaction with corporate profits. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 1950 (50); 1950 (50); 1872 (48); 1560 (40). Interpretation: At least two years after a state gubernatorial election, tax implementation is more likely when oil prices are higher. Tax enactment does not depend on U.S. macroeconomic conditions.

Figure A.7: No electoral effects on tax implementation or enactment. Description: Average marginal effects from models that interact measures of state-level political or macroeconomic conditions with our electoral cycle indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: Relative to (1a) through (2d), the estimates are more imprecise. This set of models is the only set where we find no electoral effects on tax implementation or enactment.
Figure A.7:

No electoral effects on tax implementation or enactment. Description: Average marginal effects from models that interact measures of state-level political or macroeconomic conditions with our electoral cycle indicators on tax implementation and enactment. The top panel shows the main effect for gubernatorial election years and the bottom panel shows the main effect for being in years 2 or 3 after a gubernatorial election. The omitted category is the year after an election. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: Relative to (1a) through (2d), the estimates are more imprecise. This set of models is the only set where we find no electoral effects on tax implementation or enactment.

Figure A.8: No effect of state political or economic conditions in gubernatorial election years. Description: Average marginal effects from models with our election indicators interacted with measures of state economic and political conditions. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: We find that the effect of elections on tax enactment or implementation does not depend on state economic or political conditions.
Figure A.8:

No effect of state political or economic conditions in gubernatorial election years. Description: Average marginal effects from models with our election indicators interacted with measures of state economic and political conditions. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: We find that the effect of elections on tax enactment or implementation does not depend on state economic or political conditions.

Figure A.9: No effect of state political or economic conditions on tax implementation or enactment at least two years after an election. Description: Average marginal effects from models with our election indicators interacted with measures of state economic and political conditions. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: We find that neither tax implementation or enactment is affected by state economic or political conditions at least two years after a gubernatorial election.
Figure A.9:

No effect of state political or economic conditions on tax implementation or enactment at least two years after an election. Description: Average marginal effects from models with our election indicators interacted with measures of state economic and political conditions. Whiskers are 95 percent conventional confidence intervals. FWER-adjusted p-values for the null hypothesis that the marginal effect is equal to zero versus not are in the bottom row of text for each model in each panel. Sample sizes (clusters) for the models from left to right are 2000 (50); 2000 (50); 1911 (49); 1080 (40). Interpretation: We find that neither tax implementation or enactment is affected by state economic or political conditions at least two years after a gubernatorial election.

Table A.1:

Secondary specification controls.

Gas tax imp. CIT imp. Gas tax enac. CIT enac.
(1) (2) (3) (4)
(Cents/gal) (p.p./100) (p.p./100) (p.p./100)
%Δ GSP per capita 0.97 −0.05 0.08 0.08
(0.83) (0.62) (0.31) (0.31)
Avg. unemployment rate (%) 0.04 0.00 −0.00 0.02
(0.03) (0.01) (0.01) (0.01)
ADA score ( > 50 – more liberal) 0.00 −0.00 0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
%Δ population 0.12 −1.23 −0.08 −0.28
(3.70) (1.62) (1.28) (1.54)
%Δ drivers −0.90 −0.31 −0.24 −0.49
(0.97) (0.22) (0.22) (0.25)
%Δ gas usage −0.88 0.20 −0.55 −0.02
(0.74) (0.30) (0.32) (0.30)
%Δ income per capita −4.00 −1.00 −1.32 −0.06
(1.82) (0.67) (0.38) (0.51)
Adjusted R 2 0.04 0.01
Pseudo-R 2 0.15 0.16
Observations 1950 1950 1824 1080

  1. Description: Marginal effects of control variables from equations (2a) through (2d). Clustered standard errors by state in parentheses. Statistical significance asterisks omitted.

Table A.2:

Tertiary specification controls.

Gas tax imp. CIT imp. Gas tax enac. CIT enac.
(1) (2) (3) (4)
(Cents/gal) (p.p./100) (p.p./100) (p.p./100)
Education (% college or higher) 0.25 0.05 −0.32 0.23
(0.80) (0.19) (0.28) (0.18)
News circulation (total/day) −0.00 −0.00 −0.00 0.00
(0.00) (0.00) (0.00) (0.00)
Term length (years) −0.01 −0.03 −0.02 −0.02
(0.06) (0.01) (0.01) (0.01)
%Δ oil price −0.08 0.01 −0.03 −0.02
(0.12) (0.04) (0.04) (0.02)
%Δ corporate profits −0.21 −0.06 −0.03 −0.03
(0.22) (0.06) (0.06) (0.04)
%Δ transportation usage 2.08 −0.45 −0.15 0.07
(1.44) (0.30) (0.40) (0.23)
%Δ GSP per capita 1.35 0.16 −0.06 0.04
(1.24) (0.53) (0.21) (0.14)
Avg. unemployment rate (%) 0.05 0.02 0.01 0.01
(0.02) (0.01) (0.00) (0.00)
ADA score ( > 50 – more liberal) 0.00 −0.00 0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
%Δ population −3.56 −0.94 −1.21 −1.30
(3.60) (1.12) (0.92) (0.59)
%Δ drivers −1.23 −0.23 −0.29 −0.28
(1.18) (0.18) (0.27) (0.13)
%Δ gas usage −1.21 −0.08 −0.69 −0.09
(0.94) (0.26) (0.30) (0.19)
%Δ income per capita −2.75 −0.31 −0.05 0.04
(1.73) (0.54) (0.38) (0.27)
Adjusted R 2 0.02 0.00
Pseudo-R 2 0.05 0.09
Observations 1450 1450 1450 1450

  1. Description: Marginal effects of control variables from equations (3a) through (3d). Clustered standard errors by state in parentheses. Statistical significance asterisks omitted.

Table A.3:

Election effect heterogeneity by voter attentiveness controls.

Gas tax imp. CIT imp. Gas tax enac. CIT enac.
(1) (2) (3) (4)
(Cents/gal) (p.p./100) (p.p./100) (p.p./100)
%Δ GSP per capita 0.63 −0.07 −0.07 −0.00
(0.88) (0.62) (0.20) (0.22)
Avg. unemployment rate (%) 0.01 0.00 −0.01 0.01
(0.02) (0.01) (0.01) (0.00)
ADA score ( > 50 – more liberal) 0.00 −0.00 0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
%Δ population −0.51 −1.27 −0.92 −1.82
(2.55) (1.23) (0.73) (0.84)
%Δ drivers −1.09 −0.29 −0.26 −0.37
(0.94) (0.21) (0.19) (0.18)
%Δ gas usage −1.06 0.17 −0.46 −0.09
(0.69) (0.30) (0.26) (0.25)
%Δ income per capita −3.72 −0.93 −1.18 0.06
(1.79) (0.65) (0.34) (0.41)
Education (% college or higher) 0.26 0.52 −0.52 0.52
(1.33) (0.36) (0.29) (0.32)
News circulation (total/day) −0.00 −0.00 −0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
Adjusted R 2 0.06 0.02
Pseudo-R 2 0.13 0.11
Observations 1950 1950 1900 1350

  1. Description: Marginal effects of control variables from our models that look at whether voter attentiveness affects the electoral cycle. Clustered standard errors by state in parentheses. Statistical significance asterisks omitted.

Table A.4:

Election effect heterogeneity by macroeconomic conditions controls.

Gas tax imp. CIT imp. Gas tax enac. CIT enac.
(1) (2) (3) (4)
(Cents/gal) (p.p./100) (p.p./100) (p.p./100)
%Δ GSP per capita 1.51 0.15 0.73 0.23
(1.01) (0.53) (0.25) (0.18)
Avg. unemployment rate (%) 0.04 0.02 0.01 0.02
(0.02) (0.01) (0.00) (0.00)
ADA score ( > 50 – more liberal) 0.00 −0.00 0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
%Δ population −7.00 −0.29 −1.93 −0.42
(4.23) (1.29) (1.04) (0.88)
%Δ drivers −0.81 −0.13 −0.22 −0.22
(1.02) (0.21) (0.25) (0.14)
%Δ gas usage −0.87 0.01 −0.63 −0.09
(0.73) (0.26) (0.28) (0.19)
%Δ income per capita −0.90 0.05 −0.22 −0.02
(1.03) (0.47) (0.29) (0.24)
%Δ oil price −0.75 −0.15 −0.14 −0.05
(0.29) (0.09) (0.07) (0.05)
%Δ corporate profits 0.45 0.00 0.04 −0.04
(0.31) (0.12) (0.09) (0.07)
Adjusted R 2 −0.00 −0.00
Pseudo-R 2 0.07 0.15
Observations 1950 1950 1872 1560

  1. Description: Marginal effects of control variables from our models that look at whether macroeconomic conditions affect the electoral cycle. Clustered standard errors by state in parentheses. Statistical significance asterisks omitted.

Table A.5:

Election effect heterogeneity by state-level political or economic conditions controls.

Gas tax imp. CIT imp. Gas tax enac. CIT enac.
(1) (2) (3) (4)
(Cents/gal) (p.p./100) (p.p./100) (p.p./100)
%Δ GSP per capita 1.39 −1.04 −0.18 −0.48
(1.43) (0.74) (0.44) (0.28)
Avg. unemployment rate (%) 0.06 0.00 0.01 0.02
(0.04) (0.01) (0.01) (0.01)
ADA score ( > 50 – more liberal) 0.00 −0.00 0.00 −0.00
(0.00) (0.00) (0.00) (0.00)
Adjusted R 2 0.03 0.01
Pseudo-R 2 0.15 0.17
Observations 2000 2000 1911 1080

  1. Description: Marginal effects of control variables from our models that look at whether state-level economic conditions or ideological bent affect the electoral cycle. Clustered standard errors by state in parentheses. Statistical significance asterisks omitted.

Appendix B: Controls Descriptions

This section lists our control variables. We report and fix the data versions, as data can revise and lead to different estimation results (Chang and Li 2018). Subscript i indicates a state and subscript t indicates a year.

B.1 Time-Invariant Variables (X i )

  1. Education – Share of population with a four-year college degree or higher, averaged from 2003 to 2017. E d u i 2003 − 2017 ̄ . Source: U.S. Census Bureau (2018).

    1. Note: 2003–17 is due to web availability of CPS data.

  2. Newspaper Circulation Total – Daily news – 2010 rate. News i . Source: & 2018.

  3. Legislative Terms – Number of years in governor’s term (years, not years remaining). Terms it . Source: Klarner (2013a).

    1. Note: This variable has some, but limited, time-series variation, so we include it in the matrix (X i ) but denote it subscript it.

B.2 Cross-Sectionally Invariant Variables (X t )

  1. Percent Change in Crude Oil Price – Domestic first purchase price per barrel, nominal. %ΔOil t . Source: U.S. Energy Information Administration (EIA) (2018).

  2. Corporate Profits – Percent change in non-financial corporate profits, before tax (without IVA and CCAdj), nominal. %ΔProf t . Source: Federal Reserve Economic Data (FRED) (2018a).

  3. Transportation Usage – Vehicle total miles, millions per year (sum of Bus, Commuter Bus, and Bus Rapid Transit), percent change. %ΔTrans t . Source: America Public Transportation 2018.

B.3 Variables that Vary over Time and Across States (X it )

  1. Gross State Product (GSP) – Percent change, nominal. %ΔGSP it . Source: Bureau of Economic Analysis (BEA) (2018).

  2. Unemployment Rate – State percentage of people unemployed – Average of monthly, seasonally adjusted rates. UnempRate it . Source: Federal Reserve Economic Data (FRED) (2018d).

  3. Voter Preferences – Adjusted Americans for Democratic Actions (ADA) scores – average score across all elected officials. VoterPref it .

    1. Source: Independently tabulated by Groseclose, Levitt, and Snyder (1999) (for 1947–1998 originally and later extended by Groseclose to 2008) and by Anderson and Habel (2009) (for 1947–2007); updated and reconciled by Justin Briggs (2008–2015). We use the adjusted ADA score that removes errors in the original ADA score using data from Dr. Groseclose.

  4. Resident Population – All residents (both civilian and Armed Forces) living in the state, percent change. %ΔPop it . Source: Federal Reserve Economic Data (FRED) (2018c).

  5. Licensed Drivers – Number of licensed drivers, percent change. %ΔDrivers it . Source: U.S. Department of Transportation, Office of Highway Policy Information (2016b).

  6. Highway Use of Gasoline – Thousands of gallons, percent change. %ΔGasUsage it . Source: U.S. Department of Transportation, Office of Highway Policy Information (2016a).

  7. Per Capita Income – Income per person, nominal, percent change. %ΔIncPerCap it . Source: Federal Reserve Economic Data (FRED) (2018b).

Appendix C: Do Election Effects Depend on Political, Demographic, or Economic Conditions?

This appendix reports the models that we used to investigate whether elections have different effects on tax implementation or enactment based on political, demographic, or macroeconomic conditions that we specified in our pre-analysis plan (Chang et al. 2019). Largely, these models show that this electoral effect does not depend on these factors.

For brevity we focus this explanation on the electoral variables, which are our variables of interest, and omit a discussion of the controls.

C.1 Do the Effects of Elections on Tax Implementation or Enactment Depend on Voter Attentiveness?

The first set of our heterogeneity-seeking models asks whether the election effect varies with measures of voter’s attentiveness to new legislation, which we proxy with the average education level in a state, E d u i 2003 − 2017 ̄ and the average daily newspaper circulation, News i . We add the interaction of these proxies with our electoral variables to (2a) through (2d).

After including these interactions, Figure A.1 shows gubernatorial election years are not significantly associated with changes in the implemented gas tax or the CIT. Nor are they associated with the probability that legislation is enacted to increase the taxes. If you really want to peer into the tea leaves, then the gubernatorial election point estimates are negative for tax enactment. Economically, these point estimates suggest that gubernatorial election years may temporarily suppress gas and corporate tax rate enactment. That said, these models lack state fixed effects, so there may be confounding factors not captured by the models.

The interactions between the election indicators and both education and newspaper circulation are not statistically significant (Figures A.2 and A.3). We, therefore, do not have evidence that voter attentiveness affects the propensity for elections to reduce tax enactment and implementation. Given one of our main results – that we find larger electoral effects for enactment compared with implementation – it is a bit surprising that we find no additional effect of voter attentiveness on the electoral cycle patterns of enactment or implementation. Perhaps our measures for voter attentiveness are too crude, as we lack data to measure voter attentiveness over time and between states.

C.2 Do Effects of Elections on Tax Implementation or Enactment Depend on U.S. Macroeconomic Conditions?

We now investigate whether the propensity for state politicians to enact or implement taxes depends on U.S. macroeconomic conditions. We interact oil prices and corporate profits, separately, with our electoral cycle indicators and add these interactions to (2a) through (2d).

We see in Figure A.4 that enacted and implemented taxes are least likely and smallest, respectively, in an election year, particularly for gasoline taxes after including these interactions.

Regarding the interaction terms of our gubernatorial election indicator with oil prices and corporate profits, Figure A.5 shows no statistically significant estimates, so we conclude that U.S. macroeconomic conditions have no effect on tax implementation or tax enactment in gubernatorial election years, though the interaction term in the implemented gas tax model is rather imprecise.

There is some evidence that, when it is at least two years after a gubernatorial election, higher oil prices are associated with higher implemented (but not enacted) taxes. For the gasoline tax, a 1 percentage point increase in oil prices at least two years after a gubernatorial election causes a 0.86 cent per gallon increase in implemented gasoline taxes (p = 0.03), shown in Figure A.6. In some states the gasoline tax is linked to the net-of-tax price of gasoline, so it is possible that the model is picking up this linkage. The same effect for the CIT is 0.2 percentage points and more imprecise (p = 0.07). That said, as these models lack time fixed effects there may be omitted confounding factors.

C.3 Do the Effects of Elections on Tax Implementation or Enactment Depend on State-Level Political or Economic Conditions?

In our final set of models that look at heterogeneous election effects, we interact our electoral indicators with three state-level political and economic indicators: ADA score, gross state product (GSP), and the unemployment rate and add these interactions to (1a) through (1d).

The main electoral effects, shown in Figure A.7, indicate that none of the models with these interactions have an electoral effect. This set of models is the only set that finds no electoral effects. Furthermore, in Figures A.8 and A.9, the interaction terms of our electoral indicators with GSP, the unemployment rate, and the ADA score are not significant.

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Received: 2024-09-24
Accepted: 2025-03-28
Published Online: 2025-05-22

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Fair Choices During COVID-19: Firms’ Altruism and Inequality Aversion in Managing a Large Short-Time Work Scheme
  4. Inequality in Health Status During the COVID-19 in the UK: Does the Impact of the Second Lockdown Policy Matter?
  5. The Political Timing of Tax Policy: Evidence from U.S. States
  6. Is it a Matter of Skills? High School Choices and the Gender Gap in STEM
  7. Patent Licensing and Litigation
  8. Class Size, Student Disruption, and Academic Achievement
  9. Political Orientation and Policy Compliance: Evidence from COVID-19 Mobility Patterns in Korea
  10. Social Efficiency of Free Entry in a Vertically Related Industry with Cost and Technology Asymmetry
  11. Carbon Tax with Individuals’ Heterogeneous Environmental Concerns
  12. Equitable Redistribution and Inefficiency under Credit Rationing
  13. Letters
  14. Psychological Well-Being of Only Children: Evidence from the One-Child Policy
  15. Peer Effects in Child Work Decisions: Evidence from PROGRESA Cash Transfer Program
  16. Right Time to Focus? Time of Day and Cognitive Performance
  17. Employee Dissatisfaction and Intentions to Quit: New Evidence and Policy Recommendations
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https://doi.org/10.1515/bejeap-2024-0333
Keywords for this article
corporate income taxes; electoral cycle; gasoline tax; pre-analysis plan; political budget cycle; tax salience

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Fair Choices During COVID-19: Firms’ Altruism and Inequality Aversion in Managing a Large Short-Time Work Scheme
  4. Inequality in Health Status During the COVID-19 in the UK: Does the Impact of the Second Lockdown Policy Matter?
  5. The Political Timing of Tax Policy: Evidence from U.S. States
  6. Is it a Matter of Skills? High School Choices and the Gender Gap in STEM
  7. Patent Licensing and Litigation
  8. Class Size, Student Disruption, and Academic Achievement
  9. Political Orientation and Policy Compliance: Evidence from COVID-19 Mobility Patterns in Korea
  10. Social Efficiency of Free Entry in a Vertically Related Industry with Cost and Technology Asymmetry
  11. Carbon Tax with Individuals’ Heterogeneous Environmental Concerns
  12. Equitable Redistribution and Inefficiency under Credit Rationing
  13. Letters
  14. Psychological Well-Being of Only Children: Evidence from the One-Child Policy
  15. Peer Effects in Child Work Decisions: Evidence from PROGRESA Cash Transfer Program
  16. Right Time to Focus? Time of Day and Cognitive Performance
  17. Employee Dissatisfaction and Intentions to Quit: New Evidence and Policy Recommendations
  18. On the Stability of Common Ownership Arrangements
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