A new paper on wealth inequality from economists Emmanuel Saez and Gabriel Zucman – who have written frequently on the subject – was released earlier this month. This paper is far better than previous attempts to measure...
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New Report on Corporate Income Taxes and Employment Doesn’t Come Close
In a new report, the Center for Effective Government claims that “Lower Taxes on Corporate Profits Not Linked to Job Creation.”
How do they come to this conclusion? Using a dataset constructed by the Citizens for Tax Justice, they picked 30 profitable corporations that paid high effective tax rates and 30 profitable corporations that paid low effective tax rates between the years 2008 and 2010. They compared these two groups of corporations and observed that the 30 corporations that paid high effective tax rates created 200,000 jobs while those with low effective tax rates “shed” 51,000 jobs between the years 2008 and 2012.
This study suffers from serious methodological and data issues that need to be addressed. The report does not adjust for timing issues inherent in measuring corporate taxes, it compares unrelated statistics, and it uses flawed data.
Study Does not Adjust for Timing Issues
This study only uses a business’s current profits and tax payments as their measure of effective tax rates. They ignore any losses that may have been carried forward from previous years. U.S. tax law allows businesses that suffer losses in a given year to deduct these losses in future years in order to better reflect their actual tax burden over time.
Suppose a Christmas decorations shop makes all its money in the fall quarter, and loses money the rest of the year. Would you impose tax and measure its tax rate only on its fall gains, and not allow a deduction for the losses from January through September? Of course not.
Not accounting for this can overstate a business’s profits and make them seem like they are paying a very low effective tax rates in certain years, when they had losses in past years.
Why does this matter for this study? Corporations’ carried forward losses are correlated with both lower effective tax rates in later years (2008, 2009, and 2010) and job losses. If a company loses money in one year they will likely have a lower tax bill and cut jobs the next year. Although all 60 of these corporations were profitable between 2008 and 2010 on their financial statement, the 30 corporations that had low effective corporate tax rates may have carried-forward losses from previous years (one of those years being the 2007 recession). At the same time, these losses from 2007 may have led to these businesses laying people off.
Rather than observing any causal link between tax rates and employment, they have just stumbled upon how our tax system treats corporations that suffer losses and may have to layoff people.
Compares Apples to Oranges
They also completely fail to control for fundamental differences across industries. For instance, they find that many of the profitable companies that paid high taxes and hired many workers were retailors, while many energy, telecommunication, and technology companies were among the corporations that paid low effective rates and shed jobs. There could be many reasons for this phenomenon that has nothing to do with corporate taxes.
Retail companies may just be doing better than other industries, thus the higher profits (and taxes on those profits) and hiring in the years following the Great Recession. Related, it may also be the case that labor needs may be fundamentally different across industries. Retailors require a lot of workers and thus may have hired many employees as the recession ended. Other industries may be still shedding jobs due to the recession and hire at a slower pace due to their heavier reliance on capital over labor. Differences in labor costs also can affect a business's hiring and layoff patterns.
In fact, many have pointed out that most jobs created after the Great Recession have been low-skilled retail jobs, not high-skilled jobs that would be suited for the telecommunication and energy industries (See figure below). It is entirely unreasonable to compare companies in these two industries without controlling for fundamental differences between them.
Data on Corporate Profits and Corporate Tax Revenue are Flawed
In figure 4 of their report, they present data comparing corporate profits and corporate income taxes paid as a percent of GDP, showing that while corporate profits have increased, corporate income taxes paid has declined. The problem with this analysis is that the two datasets they are using are, again, comparing apples and oranges.
While the corporate income tax payment statistics from OMB (blue line) are those taxes paid by only C-corporations, the data on corporate profits from the Bureau of Economic Analysis (red line) are profits earned by not just C-corporations, but S corporations, REITs (real estate investment trusts), RICs (regulated investment companies), UITs (unit investment trusts), and cooperatives.
These businesses are not taxed through the corporate income tax, they are taxed through the individual income tax. The number and profitability of these firms have greatly increased in last few decades. According to the IRS, S corporate profits grew fivefold between 1988 and 2003. In 2008, S corporate profits alone accounted for 27 percent of all corporate profits.
The profits S corporations earn show up in the red line, but their taxes do not show up on the blue line. Failing to adjust for this issue in the BEA data leads to a greatly overstated difference between corporate profits and corporate income taxes paid, especially in recent decades, as the amount of pass-through income measured by the BEA has greatly increased.
The question of whether high taxes affect employment is important, especially now as politicians are looking to reform the tax code. However, this report fails to convincingly answer this question. Putting aside its data issues, its results are more a product of randomness than anything else. They use a tiny sample of corporations during a very short timeframe and recognize a pattern. Unfortunately, this pattern likely does not repeat itself if their sample were to get larger and if they were to do a more robust analysis. Their conclusion is akin to blindly picking two jellybeans from a bag of 1,000, getting two red ones, and then concluding that the rest of the jellybeans in the bag must be red.
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