Doctoral Dissertation Research: The Price Elasticity of R&D: Evidence From State Tax Policies

在2008纳税年度，联邦研发（R&amp；D）税收抵免向企业支付了超过80亿美元，占联邦研究总支出的7%。税收抵免的目的是为企业提供一种激励，以提高其研发资金的私人水平。该项目将调查税收激励在增加研发方面的有效性。这种评估是困难的，因为虽然我们可以观察到税收政策变化前后的研发支出，但我们只能推测如果没有税收政策变化，研发会是什么样子。由于政策制定者是根据当前和/或预期的经济状况来实施税收激励措施的，因此，对税收激励措施实施前后的研发进行简单比较，将导致对税收激励措施效果的不准确推断。例如，如果某一年的研发经费很低，那么政策制定者可能会以税收激励作为回应。虽然接下来一年的反弹可能是由于税收激励，但也可能反映出研发支出只是回到了平均值。或者，政策制定者可以预见到研发支出的下降，并实施税收激励措施来防止这种下降。随后观察到在税收激励发生后研发没有变化，这将是支持税收激励有效性的证据。为了纠正税收激励的内生性，我们将使用由美国联邦研发税收抵免变化驱动的州一级税收变化。各州政府在制定其独特的州一级税收政策时关注的是州一级的经济状况，而联邦政府制定的是统一的全国税收政策，对个别州的经济状况关注较少。此外，由于联邦和州税收的相互作用，联邦研发税收抵免的变化对各州的州一级税收激励产生了不同的影响。这两个特征暗示了一种回归模式，可以对税收优惠对研发的影响进行无偏估计。更广泛的影响：除了支持博士候选人的培训外，本研究还将做出几项重要贡献。首先，该项目将创建一个关于州企业税法的数据集，该数据集将比任何现有的关于州研发税收激励的数据集都更详细。这些数据将允许对研发的总体税负如何随时间和州/地区的变化进行描述性分析。其次，该项目将对税收激励如何影响研发产生公正的估计。最后的贡献将是对税收政策自我选择驱动的内生性偏差的估计，这将有助于未来关于税收激励的经济学研究，并揭示税收政策实施背后机制的证据。

In tax year 2008 the federal research and development (R&D) tax credit paid out over $8 billion to businesses, which was 7% of total federal expenditures on research. The intent of the tax credit is to provide an incentive for firms to raise their private level of R&D funding. This project will investigate how effective tax incentives are at increasing R&D. This evaluation is difficult because, while we can observe R&D spending before and after a tax policy change, we can only speculate on what R&D would have been without the tax policy change. Because policymakers implement tax incentives in response to current and/or expected economic conditions, a simple comparison of R&D before and after a tax incentive is implemented will lead to inaccurate inferences about the effects of the tax incentive. For example, if R&D in a given year is low, then policymakers may respond with a tax incentive. While a rebound in the following year could be due to the tax incentive, it might also reflect R&D simply returning to its mean value. Alternatively, policymakers might foresee a decline in R&D and implement a tax incentive to prevent the decline. Subsequently observing no change in R&D after the tax incentive takes place would be evidence supporting the efficacy of the tax incentive.To correct for the endogeneity of tax incentives, we will use state-level tax variation driven by changes in the U.S. federal R&D tax credit. While state governments are attentive to state-level economic conditions when forming their idiosyncratic state-level tax policies, the federal government sets a uniform national tax policy and is less attentive to individual state economic conditions. In addition, changes in the federal R&D tax credit have differential impacts on state-level tax incentives across states due to the interaction of federal and state taxes. These two features imply a regression mode that can generate an unbiased estimate of the effect of tax incentives on R&D.Broader Impacts: This study will make several important contributions, in addition to supporting the training of a doctoral candidate. First, the project will create a dataset on state corporate tax laws that will be more detailed than any existing dataset on state R&D tax incentives. These data will allow a descriptive analysis of how the overall tax burden for R&D has changed over time and across states/regions. Second, the project will generate an unbiased estimate of how tax incentives affect R&D. The final contribution will be an estimate of the endogeneity bias driven by self-selection of tax policies, which will help future economic research on tax incentives and uncover evidence on mechanisms behind the implementation of tax policies.