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This paper examines the optimal use of tax incentives relating to the Hawaii sales, use and excise tax. While many states offer exemptions to these taxes, Hawaii is the only known state that ties its excise tax credit to the depreciation method used on the state income tax return. Therefore, the purpose of this study is to use the Hawaii business tax context to illustrate the complex trade-offs and year-by-year analyses that small businesses often must employ in the presence of shifting federal tax policy that indirectly influences state tax structures because of tax coupling. Federal and Hawaii taxpayers can elect to expense depreciable property using the 179 expensing provision or to depreciate using the modified accelerated cost recovery system (MACRS). We develop a model that will help non-corporate small businesses in Hawaii determine their optimal tax cost recovery strategy: (1) Utilize Hawaii Section 179 immediate expensing on purchases of tangible personal property, or alternatively (2) Employ MACRS depreciation on these purchases combined with the Hawaii Capital Goods Excise Credit. Our modeling separately considers the possibility that the proprietor jointly makes the federal and Hawaii cost recovery decision, as well as the alternative possibility that these cost recovery decisions are made independently.

The study illustrates that the interaction of federal and state law differences exacerbated by frequent tax changes may cause significant tax compliance complexity and resulting confusion for small non-corporate business taxpayers who are generally not equipped to wrestle with such issues. From a policy perspective, states may wish to minimize complexity using coupling efforts with federal law or otherwise routinely revisit outdated state tax statutes that indirectly cause unintended tax consequences. States must be cognizant, however, that their own budget constraints may worsen if they fully couple with recent generous federal Section 179 expensing limits.

The purpose of this paper is to examine the impact of changes in farm economic conditions and macroeconomic trends on US farm capital expenditures between 1996 and 2013.

A synthetic panel is constructed from Agricultural Resource Management Survey (ARMS) data. A dynamic system GMM regression model is estimated for farms as a whole and separately within farm typology categories. The use of farm typologies allows for comparison of the relative magnitudes of these estimates across farms by farm sales level and the operator’s primary occupation.

Changes in gross farm income levels, tax depreciation rates, and interest rates have a significant impact on crop farm investment, while changes in output prices, net cash farm income levels, tax depreciation rates, and farm specialization levels have significant impacts on livestock farm capital investment. The relative significance and magnitudes of these impacts differ within farm typologies. Significant differences include a greater responsiveness to change in tax policy variables for residential crop farms, greater responsiveness to changes in output prices and debt to asset ratios for intermediate livestock farms, and larger changes in commercial crop and livestock farm investment given equivalent changes in farm sales or the returns to investment.

These findings are of interest to agricultural economists when constructing farm investment models and employing pseudo panel methods, to those in the agricultural equipment and manufacturing sector when constructing models to manage inventories and plan for production needs across regions and over time, to those involved in drafting tax policy and evaluating the potential impacts of tax changes on agricultural investment, and for those in the agricultural lending sector when designing and executing agricultural capital lending programs.

This study uniquely identifies differences in the level of investment and the magnitude of investment responsiveness to changes in farm economic conditions and macroeconomic trends given differences in income levels and primary operator occupation. In addition, this study is one of the few which utilizes ARMS data to study farm capital investment. Utilizing ARMS data provides a rich panel data set, covering producers across many different crop production types and regions. Finally, employing pseudo panel construction methods contributes to efforts to effectively employ cross-sectional data and dynamic models to study farm behavior across time.

On October 9–10, 1975, representatives from approximately 75 companies in the United States, Canada, and Mexico attended a symposium in New Orleans entitled “The Future of Corporate Planning Models.” The symposium, sponsored by the Corporate Modeling Users Group of Social Systems, Inc., featured 13 presentations on the application of corporate planning models.

The success of a manufacturing corporation mostly depends on its production decisions. The selection of production levels is a primary responsibility of management who should select production levels that maximize the discounted value of the cash‐flow stream (NPV) resulting from the production projects. As a result, the need to evaluate the cash‐flow stream for various production levels is becoming more frequent. Provides an explicit model for the economic evaluation of various attainable production levels. The model, developed in this study, under the condition of a time‐dependent elastic demand, for each year compares a series of gross incomes G, that results from the various attainable production amounts Q, with a corresponding series of minimum annual revenue requirements R. Based on these comparisons, it identifies the optimal production level and the unit selling price for a particular year where G‐R is a maximum and finally, based on the maximum G‐R values, it determines the NPV value. A computer program (written in PASCAL) is provided to implement the model on either a TI or IBM. The program is capable of displaying and printing the results. Because of the use of several levels of nesting, the top‐down programming technique is used in its design and implementation.

The purpose of this case is to allow students the opportunity to examine how the recent changes to depreciation incentives in the Tax Cuts and Jobs Act of 2017 (P.L. 115-97, Dec. 22, 2017) may affect the purchase of capital assets. Bonus depreciation has been extended to allow an immediate 100% deduction for eligible property, which also now includes used property. This bonus depreciation will be phased out over a nine-year period. Additionally, the progressive marginal tax rate used for business income has been eliminated and replaced by a flat 21% tax rate, representing a 14% drop in the tax rate on businesses.

Specifically, this case will examine how a change from 50% to 100% bonus depreciation affects purchasing decisions between asset classes, due to the exaggerated impact on the net present value for longer lived assets. In keeping with the evolution of accounting in academia, students will be asked both to solve a realistic problem and to communicate their investment decisions effectively. To prepare students for the assignment, the informational building blocks are presented in modules following Bloom’s taxonomy – culminating in the application of the concepts in a decision-making scenario. The learning method applied in this case has been tested in the classroom, with quantifiable results showing a positive learning outcome. Pre- and post-case assessment questions were administered with significant improvement in students reported understanding across all six measures. Based on these results, this case achieves the dual goals of teaching students how to apply the concept of bonus depreciation to maximize value and how to communicate this information effectively.

This research quantifies the economic impact of regional tax policy incentives included in the Gulf Opportunity Zone Act of 2005.

This research utilized linear mixed-effects modeling and multiple regression procedures with a matched sample panel dataset from 2002 through 2008 containing real-world county-level economic data.

The results indicated that the regional tax incentives provided by the GO Zone Act did not generate significant increases in key economic indicators included in this study. These tax incentives were intended to spur economic recovery, but based on research findings, they do not appear to have had the impact desired by Congress.

Archival empirical data for the affected region make this study possible but also limit the ability to generalize these results to other regions. In addition, empirical research utilizing real-world data can be prone to internal validity issues that exist due to lack of environmental controls and other possible causal factors.

This research adds to the existing literature by using real-world county-level economic indicators to test the impact of tax policy investment incentives at the regional level and minimizes some of the issues addressed by prior empirical research and provides evidence on the effectiveness of tax policy investment incentives at the regional level.

Bonus depreciation was enacted by the United States Congress and signed into law in 2002 largely in response to the economic malaise that engulfed the U.S. economy after the September 11, 2001 terrorist attacks. We investigate whether bonus depreciation, a capital asset expensing allowance under the U.S. federal income tax code, impacts the level of business investment in property, plant, and equipment in the time periods that followed 9-11 in comparison to other earlier time periods. Based on the empirical evidence, the bonus depreciation policy has a positive effect on capital expenditures only in the period in which this policy was legislatively anticipated, specifically the period spanning the last quarter of 2001 and the first quarter of 2002. Otherwise, we find no significant increase in capital expenditures during the period that this special depreciation provision policy is initially in place from 2002 to 2005. Although bonus depreciation is re-enacted in response to the fiscal distress and recession that began in 2007, capital expenditures actually decline during the recovery era, a period following the post-2008 subprime mortgage crisis. Though Congress continues to temporarily re-enact bonus depreciation on an annual basis through December 31, 2014, there is no strong evidence that capital investment is positively impacted. Instead, the empirical results show that factors that positively affect the level of companies’ capital expenditures include capital intensity, cost of capital, amount of cash holdings, changes in sales and loans. Our empirical results invite the question of Congress’ intended goal in re-instating bonus depreciation for 2015 through 2019.

The use of corporate aircraft has increased as businesses place more value on ease of mobility. The bonus depreciation incentives of 2002 and 2003 provided growth opportunities for the general aviation market by allowing accelerated depreciation deductions for the purchase of new corporate aircraft. These incentives allowed more than twice the traditional MACRS allowance for depreciation for the first year of operation of an asset, but the present value of the tax savings after the full depreciable life of the corporate aircraft only generated a 3.25 percent reduction in the after-tax-cost. This study documents that the bonus depreciation incentives did not generate significant growth in the general aviation aircraft market via increased production of aircraft. These incentives may have simply slowed the recession that might have taken place in this industry otherwise. However, the incentives in this study did play a significant role in determining which type of aircraft to purchase, piston or turbine.

When a small business purchases a capital asset, its cost for tax purposes is spread over the useful life of the asset through the process of depreciation. It has become common in the USA for policy makers to enhance depreciation rules in an effort to increase business investment in a less-costly manner than across-the-board marginal tax rate cuts. Indeed, short-term depreciation policies are often billed by policy makers as a way to save America's small businesses. However, little is known about the actual effects of depreciation policies on small business activity. This paper aims to discuss these issues.

In this initial attempt to test the political claims regarding the importance of depreciation rules, the paper uses a 12-year panel of tax returns for Schedule C sole proprietors to empirically examine whether more generous depreciation policies influence small business activity at the extensive margin. Specifically, the paper estimates a series of multivariate models to explain sole proprietors’ decisions to remain in business as functions of their financial, demographic, and tax situations, including measures of the present discounted value (PDV) of a stream of tax deductions for depreciated capital under various rule structures.

Throughout the analysis, the authors are unable to find evidence that favorable depreciation rules lead to greater rates of entrepreneurial longevity among Schedule C sole proprietors.

Discrete choice results suggest that increases in the PDV of tax reductions from depreciation (e.g. depreciating the value earlier in the recovery period) might actually lead to higher probabilities of small business exit, while survival analysis finds no clear influence of depreciation on spells of small business activity.

The purpose of this paper is to estimate the impact of Internal Revenue Code cost recovery provisions – Section 179 and “bonus depreciation” – on farm capital investment.

The authors construct a synthetic panel of data consisting of cohorts of similar farms based on state and production specialization using the USDA’s Agricultural Resource Management Survey for years 1996-2012. Employing panel data methods, the authors are able to control for time-invariant fixed effects, as well as the effects of past investment on current investment.

The authors estimate statistically significant investment demand elasticities with respect to the Section 179 expensing deduction of between 0.28 and 0.50. A change in bonus depreciation, on average, had little impact on capital investment.

The estimates suggest there is a modest effect of the cost recovery provisions on investment overall, but a stronger effect on farms that have more than $10,000 in gross cash farm income. There are other implications for the agricultural sector: the provisions may encourage technology adoption with its associated benefits, such as reduced cost of production and improved conservation practices. On the other hand, the policy could contribute to the growing concentration in production as large commercial farms expand their operated acreage to take advantage of increasingly efficient physical capital.

To the authors’ knowledge, this is the first research to use a nationally representative dataset to estimate to impact of Section 179 and “bonus depreciation” on farm investment. The findings provide evidence of the provisions’ impact on farm capital purchases.