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Previous articleNext article FreeSummaries of ArticlesSummaries of ArticlesPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMorePrice Isn’t Everything: Behavioral Response Around Changes In Sin TaxesAlex Rees-Jones and Kyle RozemaTaxes change behavior. But how does this change arise? In traditional economic models, change is achieved through the price channel: assuming all else is held constant, taxes increase prices and thus decrease demand. However, the assumption that all else is held constant may be violated in the course of a change in tax law, in part because the process by which laws are changed often involves the provision of information, attempts at persuasion, and the deployment of alternative dissuasive tools. Although one may expect these alternative channels to be important, relatively little empirical work measures the relative importance of them compared to a tax’s direct financial influence.In this article, we study the importance of nonprice factors in a particular policy domain: discouraging smoking with cigarette taxes. Examining state-level cigarette tax changes occurring between 1989 and 2009, we document the time paths of tobacco-industry-related political donations, antismoking appropriations, cigarette-related news headlines, and legislation of place-based smoking restrictions. We find that these nonprice factors are changing during windows when tax changes occur. To explore how this evolution of nonprice factors matters for estimates of behavioral change, we make use of information on the cigarette consumption of new mothers reported in the Vital Statistics Detailed Natality Data. In this population, we conduct common analyses that measure the degree to which cigarette consumption responds to the increase in cigarette taxes in the window around a tax change. We find that controlling for nonprice factors substantially reduces the estimated responsivity of consumption to tax changes. In addition, because these nonprice factors evolve in advance of a tax change, they can generate a decrease in consumption in advance of the actual tax-induced price change. This anticipatory decline in consumption closely resembles that predicted by “rational-addiction” motives, but it is derived from a different underlying behavioral model.Taken together, our results suggest an important role of nonprice factors in understanding the evolution of cigarette consumption that occurs around a tax change. We conclude by discussing the implications of our results for forecasting the expected effects of tax policies and for assessing estimates of sin-tax elasticities.Revealing Values: Applying the Inverse-Optimum Method to Us State TaxesRobert EmbreeSystems of tax rates represent a major mechanism by which societies implement their social preferences about inequality and redistribution. Observing different income tax rates in two jurisdictions may be a consequence of differences in social preferences; however, it may also reflect differences in income distributions or forms of progressivity present in other parts of the tax system. Optimal income tax policy tells us that having higher income inequality suggests higher tax rates on the rich for any given social welfare preferences.The inverse-optimum approach to tax policy reverses the optimal income tax method and uses existing tax rates to infer marginal social welfare weights for each income level. These weights reveal information about underlying philosophical preferences and are obtained from a calculation that considers both tax rates and income inequality. Lockwood and Weinzierl (2016) have used the inverse-optimum to examine US federal income taxes.In this paper, I apply the inverse-optimum method to US state tax data. Using IRS tax data, I calculate the implied weights for single and joint filers in each income group for every US state and make three main contributions to the literature. First, I extend the theory underlying the inverse-optimum method to include the effects of commodity taxation, such as sales and property taxes. Second, I calculate effective marginal income tax and commodity tax rates for each state and income level. I use federal, state, and local income taxes; federal payroll taxes; state and local sales taxes; and state and local property taxes. I consider tax deductions and the tax treatment of different sources of income.Third, I apply my inverse-optimum methodology to both single and joint filers and to all 50 US states and the District of Columbia in the 2016 tax year. I find decreasing weights for both single and joint filers. Notably, the pattern of weights is much flatter than most philosophies of social welfare might assume because weights above $100,000 decline very little. I show how state income tax rates can be explained by differences in both preferences and income inequality. I observe substantial differences in progressivity across states, finding that the ratio of the top-to-median weights varying from a low of 0.48 in New Jersey to a high of 0.72 in Nevada. I also find that every state has a nonmonotonic pattern of weights but that some states have much larger nonmonotonicities.Returns to Scale in Property Assessment: Evidence from New York State’s Small Localities Coordination ProgramYusun Kim, Yilin Hou, and John YingerProperty assessment determines the taxable value of each parcel of real property; it is a key component of property tax administration. The property tax is the main own-source revenue for local governments in the United States, and local jurisdictions responsible for assessment vary widely in parcel size both within and across the 50 states. This variation leads to a question: What jurisdiction size maximizes productive efficiency in assessment? This study provides an up-to-date answer to this question based on a natural experiment in New York State (NYS).This experiment arises because the NYS Coordinated Assessment Program (CAP) incentivizes cities and towns to merge their assessment functions while maintaining separate taxing authority. This study takes advantage of cooperative agreements among small jurisdictions, which lead to changes in parcel counts, to estimate the extent to which the assessing function is characterized by economies of parcel scale. This estimate indicates whether the existing boundaries of assessing units correspond to the boundaries that minimize the cost of assessing properties — and thereby informs future cooperation or consolidation decisions.In this paper, we focus on jurisdiction size measured by the number of parcels as our scale dimension to identify economies of size in property assessment, which are said to exist when the per-parcel assessment cost falls as jurisdiction size increases, holding assessment quality constant. We estimate the magnitude of returns to parcel scale using a panel data set of NYS assessing jurisdictions from 2003 to 2014. We find that combining the assessment function between two identical jurisdictions with 10,000 parcels each reduces assessment cost by 46 percent. We also estimate potential cost savings from centralizing the assessment function to the county level. If 20 median-sized jurisdictions (each with 2,391 parcels) decide to conduct countywide assessment, we estimate the average assessment cost may decline from $16.85 to $1.07 per parcel.Our results indicate how much money could be saved by consolidation of or cooperative agreements between assessing jurisdictions. They also delineate the extent to which households residing in assessing units of varying sizes must pay different amounts for the same quality of assessments. Our estimates apply to NYS, but our methods could be used in other states and are particularly relevant in the 17 states where property tax is administered at the subcounty level.Tax Credit Refundability and Child Care Prices: Evidence from CaliforniaLuke P. RodgersIn a progressive income tax system, low-income households have lower income tax liabilities, which limits the value of nonrefundable tax credits. This pattern leads to a common critique that nonrefundable tax credits provide fewer benefits for households most in need of support. An equally common proposal is to turn nonrefundable tax credits into refundable tax credits. Such a reform would sever the link between a household’s tax liability and their benefit amount, resulting in more resources being transferred to low-income households. Costs often dominate the refundability debate, yet how much low-income households would benefit from refundability depends on the incidence of the credit in question. Suppliers of goods and services consumed by low-income households may raise prices in response to increased tax credit generosity. How much of the benefit accrues to households versus suppliers should be central to the discussion about refundability. Calls for refundability frequently focus on the Child and Dependent Care Credit (CDCC), a federal tax credit available to offset child care expenses incurred by working parents. Many states offer additional child care tax credits with varying degrees of generosity and differences in refundability. California provides a unique opportunity to study how eliminating refundability of child care tax credits affects child care prices while holding other policy dimensions fixed. Using county-level price and tax return data, this study exploits the fact that the statewide policy was more consequential in areas with more lower-income families. The analysis indicates that lower credit amounts are considerably offset by lower child care prices. The estimated price response to refundability is concentrated in younger age groups and in child care centers rather than family care homes. If the price response is symmetrical and quality adjustments are limited, refundability may benefit low-income families less than the cost of the program would suggest. More generally, the decision to reclassify a tax credit as refundable should be informed by incidence considerations and the viability of alternative policy options. Previous articleNext article DetailsFiguresReferencesCited by National Tax Journal Volume 76, Number 1March 2023 Published for: The National Tax Association Article DOIhttps://doi.org/10.1086/724863 © 2023 National Tax Association. All rights reserved.PDF download Crossref reports no articles citing this article.