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Influences on the pattern of internal migration in the US, including economic factors, quality-of-life factors and public policy variables have been extensively studied by regional scientists since the early 1970s. Interestingly, a small number of studies also address the effects of economic freedom on migration. The purpose of this paper is to add to the migration literature by examining the impact of labor market freedom on both gross and net state in-migration over the study period 2008–2016.

This study uses dynamic panel data analysis to investigate the impact of labor market freedom on both gross and net state in-migration over the study period 2008–2016.

The panel generalized method of moments analysis reveals that overall labor market freedom exercised a positive and statistically significant impact on both measures of state in-migration over the study period. The study finds a 1 percentage point increase in the overall labor market freedom index results in a 2.8 percent increase in the gross in-migration rate.

The findings imply states interested in attracting migrants and stimulating economic growth should pursue policies consistent with increased labor freedom.

The emphasis in the present study is on the impact of labor market freedom on state-level in-migration patterns, both gross and net, over a contemporary time period that includes both the Great Recession and subsequent recovering.

Using Cointegration Tests, Granger‐Causality Tests, and OLS, this study empirically investigates the determinants of the rate of return on savings and loan assets over the 1965–1991 period. It is found that it is determined by the mortgage rate, the capital/asset ratio, the price of imported crude oil, the cost of deposits, and the ceiling on federal deposit insurance.

The purpose of this study is to provide new empirical evidence on the impact of a variety of financial market forces on the ex post real cost of funds to corporations, namely, the ex post real interest rate yield on AAA-rated long-term corporate bonds in the USA. The study is couched within an open-economy loanable funds model, and it adopts annual data for the period 1973-2013, so that the results are current while being applicable only for the post-Bretton Woods era. The auto-regressive two-stage least squares (2SLS) and generalized method of moments (GMM) estimations reveal that the ex post real interest rate yield on AAA-rated long-term corporate bonds in the USA was an increasing function of the ex post real interest rate yields on six-month Treasury bills, seven-year Treasury notes, high-grade municipal bonds and the Moody’s BAA-rated corporate bonds, while being a decreasing function of the monetary base as a per cent of gross domestic product (GDP) and net financial capital inflows as a per cent of GDP. Finally, additional estimates reveal that the higher the budget deficit as a per cent of GDP, the higher the ex post real interest rate on AAA-rated long-term corporate bonds.

After developing an initial open-economy loanable funds model, the empirical dimension of the study involves auto-regressive, two-stage least squares and GMM estimates. The model is then expanded to include the federal budget deficit, and new AR/2SLS and GMM estimates are provided.

The AR/2SLS and GMM (generalized method of moments) estimations reveal that the ex post real interest rate yield on AAA-rated long-term corporate bonds in the USA was an increasing function of the ex post real interest rate yields on six-month Treasury bills, seven-year Treasury notes, high-grade municipal bonds and the Moody’s BAA-rated corporate bonds, while being a decreasing function of the monetary base as a per cent of GDP and net financial capital inflows as a per cent of GDP. Finally, additional estimates reveal that the higher the budget deficit as a per cent of GDP, the higher the ex post real interest rate on AAA-rated long -term corporate bonds.

The author is unaware of a study that adopts this particular set of real interest rates along with net capital inflows and the monetary base as a per cent of GDP and net capital inflows. Also, the data run through 2013. There have been only studies of deficits and real interest rates in the past few years.

This study aims to identify factors influencing the bank failure rate in the USA over the period from 1970 to 2014 with an emphasis on economic/financial factors on the one hand and on banking legislation on the other hand. Regarding the latter, this study empirically investigates four major banking statutes: the Community Reinvestment Act of 1977; the Depository Institutions Deregulation and Monetary Control Act of 1980; the Federal Deposit Insurance Corporation Improvement Act of 1991; and the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994. After adopting the technique of generalized method of moments (GMM), a robustness check in the form of autoregressive conditional heteroskedasticity (ARCH) is undertaken. Overall, the estimations imply that the bank failure rate was a decreasing function of the percentage growth rate of real gross domestic product (GDP) and the real interest rate yields on both three-month US Treasury bills and 30-year fixed-rate mortgages and an increasing function of the real cost of funds. In addition, there is strong evidence that the bank failure rate was increased by provisions in the Community Reinvestment Act of 1977 and the Depository Institutions Deregulation and Monetary Control Act of 1980, whereas the bank failure rate was decreased as a result of provisions in the Federal Deposit Insurance Corporation Improvement Act of 1991 and the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994. Finally, there also is evidence that higher federal budget deficits elevated the bank failure rate.

After modeling the bank failure rate as a function of financial/economic variables and banking legislation, the times series from 1970 to 2014 is estimated by GMM and then by the ARCH techniques.

The results of the GMM and ARCH estimations imply that the bank failure rate in the US was a decreasing function of the percentage growth rate of real GDP as well as the real interest rate yields on both three-month US Treasury bills and 30-year fixed-rate mortgages and an increasing function of the real cost of funds. Furthermore, there is strong empirical support indicating that the bank failure rate was elevated by various provisions in the Community Reinvestment Act of 1977 and in the Depository Institutions Deregulation and Monetary Control Act of 1980, while the bank failure rate was reduced by certain provisions in the Federal Deposit Insurance Corporation Improvement Act of 1991 and the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994. There also is evidence that higher federal budget deficits increased the bank failure rate.

This study is the most contemporary (1970-2014) analysis of potential causes of the bank failure rate in the USA. The study also may be the first to apply the GMM and GARCH models to the problem. Also, some interesting policy implications are provided in the Conclusion.

To present a method for calculating the discount rate that teams apply to future-year draft picks relative to current-year draft picks and then apply that method to the actual draft picks and trades over the period 2011–2022.

The National Football League (NFL) Draft permits teams to trade the selection rights for current-year and future-year draft picks. We seek to calculate the discount rates associated with NFL Draft trades. With this method, we calculate the discount rate for each trade by NFL teams involving a combination of current-year and future-year draft picks since 2011, when the NFL ratified a new collective bargaining agreement that instituted a draft-pick salary scale and capped the length of draftees’ contracts.

We find that teams' annualized discount rates in trading away future-year draft picks are quite steep, averaging more than 100% per year. These steep discount rates suggest that teams are pressured by market competition to adopt a “win now” approach in devaluing the future draft choices relative to the present draft choices.

The actual discount rate for each trade is not known with certainty when the trade is transacted. This uncertainty arises because the within-round order of future-year picks is determined by teams’ future performance, which is not known at the time of the transaction.

In reporting these findings, we acknowledge the limitations of our analysis. The dataset is small, as there are on average between five and six trades per year involving current-year and future-year picks. More observations could have been included by extending the timeframe to before 2011, but we opted against doing so because the NFL’s 2011 CBA changed teams’ draft calculus by imposing a draft-pick salary scale and capping the length of draftees’ contracts. In addition, our discount rates as calculated are ex post facto in that they are calculated after the future-year drafts have been held. While these are the actual discount rates for the trades as transacted, the actual discount rate for each trade is not known with certainty when the trade is transacted. This uncertainty arises because the within-round order of future-year picks is determined by teams’ future performance, which is not known at the time of the transaction. As an aside, we also re-estimated each trade’s discount rate with an adjustment for that uncertainty, and the median discount rate for all 61 trades was still over 100% per year.

Providing insights into NFL Draft management behavior and decision-making for current-year and future-year draft picks since 2011, when the NFL ratified a new collective bargaining agreement that instituted a draft-pick salary scale and capped the length of draftees’ contracts.

The purpose of this study is to investigate the relationship between financial decisions and ownership structure by using the control contests on a sample of Italian listed companies.

The analysis adopts a balanced panel data set of 984 firm-year observations for the period of 2002-2013, with estimation using a generalized method of moments.

The results appear to confirm both the hypotheses of the alignment of interests and the entrenchment effect. The entrenchment and alignment effects are not found to be alternatives but rather are found to co-exist. The presence of a coalition of minority shareholders acts as a tool to control agency costs, particularly when the coalition is instrumental in the contestability of corporate control.

These findings suggest that minority shareholders may have a larger impact than previously identified by strategically aligning with other shareholders to form coalitions. This study provides several practical implications. First, dividend payout is not necessarily a good instrument to control and monitor agency costs. This is because the payout can be used to expropriate benefits from the minority shareholders. Second, high ownership concentration does not always reduce agency costs. Third, a non-collusive coalition can be more useful in the monitoring of agency costs than other tools, such as the debt level.

This study shows that there is considerable value to the firm when individual blockholders come together in a contestable environment and become instrumental in making business decisions. The results support the contention that contestability is an excellent deterrent to dampen the expropriation of benefits to minority shareholders. This study also provides evidence that cash holding can be a good substitute for dividends and debt in the effort to limit agency costs.

The purpose of this study is to investigate the relationship between the debt and ownership structure of a sample of Italian-listed companies to measure the role assumed in the control and monitoring of agency costs.

This study examines a balanced panel data, using both a random effects model and a generalized method of moments model to better capture any problems related to the endogeneity of the variables in the model.

The results provide evidence of a positive relationship between debt and ownership concentration on the one hand and a negative relationship between debt and institutional investors on the other hand. The debt seems to assume both functions, i.e. the disciplinary role of substitute at low levels of ownership concentration and a complementary role at high levels of ownership concentration.

This study provides three practical implications. The first is that the complementarity between debt and ownership concentration provides evidence of the entrenchment effect and tends to weaken the company financially. Second, the results also provide useful prompts to policy-makers who should encourage the presence of institutional investors. Third, the policy-makers should also encourage the expansion of the stock market to enhance the protection of shareholders, reduce private control benefits and provide Italy the same opportunities as other common and civil law countries to collect risk capital, avoiding the abuse of debt.

The empirical results suggest that ownership concentration increases the degree of corporate debt, whereas institutional investors assume the disciplinary role of monitoring and controlling agency costs. The results provide evidence of both the entrenchment effect and the alignment-of-interests hypothesis and that the expropriation theory seems to prevail over the control and monitoring role.

Bank failures are critical events that have far-reaching implications for the financial system and various stakeholders. This study aims to focus on analyzing the phenomenon of small bank failures in the USA.

This study adopts the coarsened exact matching (CEM) technique to enhance the reliability of the analysis. By matching similar observed characteristics, the CEM approach helps to address potential selectivity bias and facilitates a more accurate estimation of the treatment effect. This study uses a data set covering the period from 2000 through 2019 and includes 523 failed bank observations and 43,605 nonfailed bank observations.

The results reveal several key findings. Small banks, especially those with lower yields on earning assets, those with lower charge-offs on loans and leases, those with higher core capital ratios and those with higher Fed Funds rates are found to be more susceptible to failure.

Some results align with initial predictions, whereas others present contrasting outcomes.

This study underscores the significance of understanding the factors contributing to bank failure and emphasizes the importance of studying small bank failures in particular.

This study uses the CEM method. CEM is a comprehensive approach that combines matching, sample trimming and reweighting techniques. When applying CEM, researchers carefully select a set of core variables to achieve balance between the treated and control groups. The CEM process involves discretizing each continuous variable into distinct bins or categories, a process known as “coarsening.” It then requires an exact match among these binned variables between the treated and control units, which constitutes the matching step in CEM.

This paper to identify those states that suffered the largest job losses, largest GDP declines and the highest unemployment rates and those states whose employment levels, unemployment rates and GDP declines were smallest during the COVID-19 recession. In addition, this paper endeavors to provide at least preliminary insights into why some states faired so poorly, whereas other states suffered so little during this downturn.

This paper uses descriptive statistics and regression analysis to analyze the differences in state performance during the COVID-19 recession and recovery.

The results from the two estimated regression models suggest that where you lived determined the severity of the recession and living in a blue state negatively impacted the strength of state’s unemployment rate recovery.

This paper looks at only a two-year period starting with the COVID-19 recession and ending in December 2021.

This paper provides a regional assessment of the COVID-19 recession and recovery on both a state and regional level.

The paper uses descriptive statistics to characterize the substantial state-level differences in the relative magnitude of economic decline due to the Covid-19 recession. Regression analysis reveals that blue states experienced weaker recovery as compared to red states.

The study uses publicly available data to identify states that suffered the largest job losses and highest peak unemployment rates during the Covid-19 recession. The results are among the first to analyze the economic impact of the Covid-19 recession at the state level.