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Indicators of Saving Earned Income Tax Credit Recipients in the Twin Cities of Minnesota Leo T. Gabriel Associate Professor of Business Bethel University.

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Presentation on theme: "Indicators of Saving Earned Income Tax Credit Recipients in the Twin Cities of Minnesota Leo T. Gabriel Associate Professor of Business Bethel University."— Presentation transcript:

1 Indicators of Saving Earned Income Tax Credit Recipients in the Twin Cities of Minnesota Leo T. Gabriel Associate Professor of Business Bethel University Presentation for the MN Saves Network Sept. 13, 2007

2 Problem Literature indicates that low-income workers, which includes Earned Income Tax Credit (EITC) recipients, do not have adequate savings to meet long-term needs as suggested by economic theory.

3 Research Questions 1. What factors contribute to saving in financial assets for EITC recipients in the Twin Cities of Minnesota? 2. Is there a positive association between tax refund amounts and intending to save tax refunds?

4 Results—Research Question 1 What factors contribute to saving in financial assets for EITC recipients in the Twin Cities of Minnesota? Income Banked Race Marriage

5 Results—Research Question 2 Is there a positive association between tax refund amounts and intending to save tax refunds? There is no association between tax refund amounts and intending to save tax refunds.

6 Results  There was a low percentage of savers in this study.  Factors that contribute to a low percentage of savers: High percentage of families with income below the poverty threshold (66%) High percentage of unbanked families (26%) High percentage of Black families (46%).

7 Conclusions  Literature suggests that institutional theory explains saving behavior in low-income families: Access to financial institutions Incentives Financial education Facilitation of savings

8 Literature: Earned Income Tax Credit History of EITC  Growth of the EITC (Ventry, 2000) Consumption of EITC Refunds  Durable goods (Barrow & McGanahan, 2000)  70% consumed immediately (Edwards, 2004)

9 Literature: Earned Income Tax Credit Banked  ShoreBank saving program (Beverly et al., 2004) Savings  Economic & social mobility (Smeeding et al., 2000)  Lump sum refund (Romich & Weisner, 2000)

10 Literature: Saving Theory (LCH) Life-Cycle Hypothesis (Modigliani & Brumberg, 1954; Friedman, 1957)  Dominate theory in saving literature  Economic theory predicts that individuals will save for income over their life span.  Income, age, uncertainty, family composition, taxes, and rates of return are factors.

11 Literature: Saving Theory (Institutional) Institutional Theory ( Sherraden, 1991 ) ( Beverly & Sherraden, 1999 )  Suggests that institutions are factors in saving decisions.  Institutional factors Access Incentives Financial education Facilitation

12 Literature: Tax Policies  Reduction of saving disincentives (1996)  Individual Development Accounts (1998)  Retirement savings credit (2001)  State-level EITCs (1998- )

13 Knowledge of Saving-Low Income Decision to save in financial assets (Carney & Gale, 2001) Determinants Income Age Education Marital status Employment status Public assistance Race Banked

14 Current Trends Banking  Efforts to provide bank accounts for low income families.  Efforts encouraging direct deposit of tax refunds.

15 Research Methodology—Data  Data set from AccountAbility Minnesota (AAM)  Data set includes 2004 tax return data and responses to survey questions A sample of over 700 participants Criteria for selection:  Completed survey questions  Positive tax refund  Electronically filed tax returns  Tax returns accepted by IRS and MN Department of Revenue

16 Question 1:What factors contribute to saving decisions? Dependent Variable (binary): Indicator of savings in financial assets (saver=1, nonsaver=0). Evidence of saving: interest income, dividend income, capital gains/losses, IRA contributions, or retirement savings credit. Independent Variables: Income (three income groups) Age (three age groups) Bank Account Race (Black, Hispanic, White, Other) Public Assistance (0-5) Marital Status (married or single) Family Size (0-8)

17 Question 1:What factors contribute to saving decisions?

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23 Question 1: What factors contribute to saving decisions? Logistic Regression Results  Families with income between % of poverty were 2.3 times more likely to save than families with income below the poverty threshold.  Families with income greater than 150% of the poverty threshold were 3.8 times more likely to save than families with income below the poverty threshold.

24 Question 1: What factors contribute to saving decisions? Logistic Regression Results  Families with bank accounts were 4.5 times more likely to save than families without bank accounts.  When four outliers were removed from the data, families with bank accounts were 8 times more likely to save than families without bank accounts.

25 Question 1: What factors contribute to saving decisions? Significant Regression Results  Families who identified themselves as White were 2 times more likely to save than families that identified themselves as Black (African or African-American).

26 Question 2: Is there a positive association between tax refund amounts and intending to save tax refunds? Variables Dependent Variable (binary): Indicator of saving tax refund (saver=1, nonsaver=0) Evidence of saving: Participants indicating that the most important thing that they will do with their tax refunds is save it. Independent Variables: Combined federal and state income tax refund amount. Income, Age, Bank Account, Race, Public Assistance, Marital Status, Family Size

27 Question 2: Is there a positive association between tax refund amounts and intending to save tax refunds?

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30 Conclusions  Life-cycle hypothesis continues as the dominate theory in saving literature.  Institutional theory is becoming more prominent, especially in low-income saving literature: Access to financial institutions Incentives Financial education Facilitating savings

31 Limitations  This study does not establish a causal relationship between saving and predictor variables.

32 Limitations  Tax return data limits this study.  Tax return data does not capture all factors that contribute to saving decisions.  Other factors Education Work status Home ownership Credit history

33 Further Research  Linking EITC refunds with saving incentive programs, such as an IDA.  Evaluating programs offering bank accounts to EITC recipients.

34 Discussion and Questions


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