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Presentation on theme: "XIMENA CADENA (IDEAS42 AT HARVARD) ALEXANDRA CRISTEA (IDEAS42) HEBER DELGADO (IDEAS42) ANTOINETTE SCHOAR (MIT) Fighting Procrastination in the Workplace:"— Presentation transcript:


2 Motivation A large literature has documented the impact of behavioral biases on individual decision making, especially procrastination Laibson (1997) on hyperbolic discounting, ODonoghue and Rabin (2000) on procrastination, Fudenberg and Levine (2005) on dual selves Ariely and Wenterbroch (2002) DellaVigna and Malmendier (2006) Very limited research on planning fallacies within firms Hossain and List (2009) find impact of framing on incentives and performance Kaur, Kremer and Mullainathan (2010) study peer effects on productivity at the work place

3 Questions Do planning fallacies or procrastination affect employee behavior and performance in the workplace? Do interventions to encourage employees to plan better improve performance? or create deviations from the first best? Does the structure of (financial) incentives matter? Is it just a matter of the level (steepness) of bonuses? Does periodicity and frequency of incentives matter, e.g. are small frequent incentives more effective than large, end of period bonuses? Do non-pecuniary interventions that help employees plan have an impact on performance?

4 Time Allocation Problem at Bancamia Loan officers have multiple tasks within a month Promote bank services: Credit renewal and loans to new customers Analyze credit application and assist loan disbursement Manage delinquent accounts, collection calls Loan officers should focus on disbursal early in the month Delinquency management has to be done at the end of the month Repayment occur early in the month: cash flow management Actual distribution of disbursements was concentrated in the last week of the month

5 The Cost of Procrastination Baseline survey conducted in September 2008 finds high stress levels and dissatisfaction for existing loan officers 55% of loan officers felt that leveling out the workload would reduce stress levels Only half of them made work flow plans at the beginning of the month and follow them

6 Current Bonus System Bonuses are based on portfolio growth and quality Individual incentives to encourage different tasks Weight of incentives are roughly 25% for each task Bancamia previously introduced monthly incentives to encourage goal achievement : 5% reduction of potential commission as penalty for every week that a loan officer does not hit new loans targets consistent to monthly targets (25% each week of the 4) Goals depend on geography, prior experience of loan officer Bonuses are paid and calculated at the end of each month

7 The Intervention: Madrugador Program Introduce weekly incentives to reward loan placement during the first 2 weeks of the month Specific weekly goals for new loans and credit renewals Small positive incentives Gift certificates for movies, phone cards, restaurants etc ($15) 2% of average monthly salary Winner and runner-up got additional prize: vacation and ipod Reminders and recognition, constant feed-back Weekly meetings with branch managers to track performance Madrugador Monthly Bulletin

8 Monthly Bulletin: Reminders and Recognition

9 Setting Weekly Goals Created weekly goals aimed at achieving existing monthly goals for credit renewal and new customers Goals matched Bancamias ideal distribution of disbursal throughout the month

10 Research Design and Set up Randomized control trial with Bancamia – November 2008 to April 2009 – 61 branches in 6 regions – 31 bank branches were randomly selected to receive the treatment and 30 to be in the control and continue unchanged Intervention was designed at the branch level – Equality within branch staff – Logistics of implementing bonus system – Performance and bonuses are evaluated individually Second phase: Branch managers were included to receive incentives and help employees set weekly planning goals February 2009 to April 2009

11 Data Collection Banks IT system Loan officer performance and compensation, branch and portfolio characteristics, program winners Pre-treatment: July-October 2008 Post-treatment: November 2008- April 2009 Post–intervention: October-December 2010 Surveys: Phone interviews of loan officers Socioeconomic characteristics, stress levels, job satisfaction, work practices Conducted by a professional survey firm Baseline: September-October 2008 (98% response) Endline: May 2009 (96% response rate, 66% in both surveys)

12 Branch and Loan Officers Characteristics Total (1)Treatment (2)Control (3)Test T-C=0 (4) VariablesMean/Proportion P-values (SD) Panel A: Branch Characteristics Age of office (months)48.0456.5039.300.2057 (52.76)(57.35)(46.92) Number of credit analysts in office6.266.356.160.6636 (1.74)(1.70)(1.81) Office portfolio size (millions of US dollars)$ 2.75$ 2.88$ 2.610.3389 ($ 1.11)($ 1.18)($ 1.04) Office portfolio size (no. of credits)3104.243192.123013.430.5181 (1067.95)(1137.43)(1002.28) Office portfolio size (no. of credits/analyst)501.47512.92489.640.3940 (105.60)(128.89)(74.85) Agricultural credits (as % of outstanding credits)4.44%4.28%4.61%0.8742 (0.08)(0.07)(0.09) Delinquency rate (total)11.06%11.00%11.12%0.8842 (0.03) Panel B: Personal Characteristics (Loan Officers) Age29.4129.6629.110.3181 (5.46)(5.73)(5.12) Percentage women46.65%48.33%44.69%0.4746 (0.50) Time working at Bancamía (months)19.8919.8719.920.9806 (18.83)(21.63)(14.96) Percentage of time stressed33.36%34.93%31.54%0.2776 (0.31)(0.32)(0.29) Percentage of loan officers very satisifed with work45.88%44.50%47.49%0.5559 (0.50) Percentage of loan officers very satisfied with compensation27.60%27.80%27.37%0.9250 (0.45) Total wage (bonus plus basic wage) (US dollars)$ 799$ 786$ 8140.3087 ($ 264)($ 260)($ 268)

13 Impact on Branch Level Outcomes Difference-in- Difference strategy Measure loan disbursal, goal achievement and portfolio performance at the branch level : Branch and month fixed effects Separate treatment dummies for the first and second phase of intervention Additional dummy for post-intervention period Cluster at branch level

14 Impact on Performance Specifications include branch and month fixed effects. Robust standard errors are clustered at the branch level Dependent variable is loan officers achieving weekly targets Dependent variable is Gap Indicator (distance from ideal distribution of loan sourcing across the month) (1)(2)(3)(4)(5)(6)(7)(8)(9)(10) Treatment (Nov-Apr)0.3080.391-6.743*-6.601**-6.743* (0.282)(0.290)(3.644)(3.079)(3.601) Treatment (Nov-Jan)-0.081-0.045-3.907-3.541-3.907 (0.287)(0.280)(3.873)(3.692)(3.826) Treatment (Feb-Apr)0.698*0.854**-9.580**-9.837***-9.580** (0.373)(0.393)(4.390)(3.538)(4.336) Post Intervention-5.162 (5.264)(5.268) Loan Officers-0.034-0.036 (0.079)(0.078) Agricultural loans (%)8.3046.452199.761**212.765** (13.090)(12.555)(97.658)(95.848) Portfolio Size (Lag)0.003**0.003***0.0060.004 (0.001) (0.011) Delinquency Rate (Lag)-3.761**-4.078**57.424**59.639*** (1.663)(1.613)(22.411)(21.895) Constant-0.104 -1.954-1.92663.412*** -31.644-31.72964.976*** (0.089) (2.734)(2.640)(3.756)(3.760)(21.678)(21.134)(3.970)(3.973) Observations610 549 610 549 793 R-squared0.4620.4720.4890.5030.6910.6920.7010.7030.6500.651 Adj. R-squared0.3930.4030.4110.4250.6500.6510.6550.6570.6140.615 Number of clusters61

15 Impact on Productivity Specifications include branch and month fixed effects. Robust standard errors are clustered at the branch level Dependent Variable is Productivity= (Loan placement/ Loan Officers in the office before the start of the program) (1)(2)(3) (4)(4a)(5)(5a)(6) (7)(8)(9) Montly ProductivityProductivity Weeks 1&2Productivity Weeks 3&4 Loan Placement Productivity on: All Loans New Loans Loan Renewals All LoansNew Loans Loan Renewals All Loans New Loans Loan Renewal s Treatment (Nov-Jan)-0.3480.033-0.3810.296 0.193 0.103-0.410-0.192-0.218 (1.650)(1.177)(1.113)(0.424)(0.419)(0.280)(0.276)(0.308)(0.620)(0.400)(0.389) Treatment (Feb-Apr)0.5090.737-0.2281.045* 0.615* 0.429-0.685-0.394-0.291 (1.745)(1.268)(1.053)(0.594)(0.587)(0.361)(0.356) (0.661)(0.447)(0.358) Post-Intervention (Oct-Dec)0.1410.387 (0.577)(0.322) Constant38.935***17.052***21.884***6.044***6.085***2.640***2.852***3.404***13.469***5.857***7.615*** (0.862)(0.668)(0.611)(0.334)(0.311)(0.160)(0.161)(0.261)(0.412)(0.265)(0.250) Observations610 792610792610 R-squared0.7520.6740.8150.5920.5440.5650.5730.7120.7350.6200.784 Adj. R-squared0.7190.6310.7910.5380.4960.5080.5280.6740.7000.5700.755 Number of clusters61

16 No Effects on Delinquency Rates Dependent Variable is Delinquency Rate =Delinquent Loans/Total outstanding loans (1)(2)(3) (4)(5)(6) Current Delinquency Rates Future Delinquency (2 Months out) Total 30 days or less More than 30 days Total 30 days or less More than 30 days Treatment (Nov-Jan)0.0100.0060.0040.0080.0050.003 (0.007)(0.006)(0.003)(0.009)(0.008)(0.002) Treatment (Feb-Apr)0.0110.0060.0050.0060.0040.002 (0.009)(0.008)(0.003)(0.010)(0.009)(0.003) Constant0.023***0.014***0.009***0.026***0.022***0.005*** (0.003) (0.001)(0.003) (0.001) Observations610 488 R-squared0.8370.8250.8640.8230.8160.881 Adj. R-squared0.8160.8010.8470.7930.7860.862 Number of clusters61 Specifications include branch and month fixed effects. Robust standard errors are clustered at the branch level

17 Results Intervention was effective in changing loan officer behavior only after branch managers were included in the treatment Loan officers in treatment branches were 7o% more likely to achieve weekly goals Distance to the ideal time distribution of loan placement was significantly reduced with the program Overall monthly productivity did not change, but significant change in loan disbursal towards weeks 1 and 2 Especially for new loans, which are more tied to loan officer effort Effects on performance did not last after program stopped No impact effects on delinquency rates (loan quality)

18 Impact on Individual Level Outcomes Intervention impacted satisfaction and stress levels Measured at individual level in baseline and end-line surveys Cannot differentiate timing of impact in first and second phase Cluster at branch level Results Loan officers in treatment branches were 5-6% more satisfied with work and compensation More likely to make plans and follow them (8%) and felt less stressed (5%)

19 Impact on Satisfaction ProbitOrdered ProbitProbitOrdered Probit Dependent Variable (DV) is: Very satisfied or satisfied with work Satisfaction with work scale (1-5) Very satisfied or satisfied with compensation Satisfaction with compensation scale (1-5) (1)(2)(3)(4)(5)(6)(7)(8) Treatment0.2750.298*0.2000.238*0.3180.358*0.302**0.310** (0.178)(0.172)(0.145)(0.135)(0.194)(0.199)(0.149)(0.153) DV at Baseline1.268***1.625***0.627***0.708***0.572***0.522***0.444***0.468*** (0.319)(0.336)(0.108) (0.196)(0.198)(0.103)(0.104) Age0.061***0.0190.0100.022 (0.022)(0.012)(0.021)(0.016) Female-0.0490.172-0.335*-0.215 (0.182)(0.147)(0.173)(0.151) Marital Status-0.127-0.207-0.212-0.286* (0.202)(0.152)(0.212)(0.167) Dependency (% house expenses)0.4270.579**0.4290.171 (0.310)(0.248)(0.266)(0.221) Education (years)0.0710.040-0.0080.004 (0.062)(0.052)(0.049)(0.046) Time working at the bank-0.003-0.0010.0010.002 (0.004)(0.003)(0.004)(0.003) Observations254 252 Pseudo R-squared0.0670.1240.0570.0840.0420.0700.0530.074 Number of clusters61 Robust standard errors are clustered at the branch level

20 Impact on Planning and Stress Levels Planning: ProbitsStress: OLS Dependent Variable (DV) is: Make a plan and follow it Planning increased or stayed high % of time feeling stressed about work (1)(2)(3)(4)(5)(6) Treatment0.2510.296*0.2210.261*-0.058*-0.054 (0.167)(0.176)(0.141)(0.140)(0.032)(0.033) DV at Baseline0.442***0.486***0.461***0.455*** (0.168)(0.179)(0.056)(0.058) Age-0.014-0.004-0.005 (0.017)(0.020)(0.003) Female0.0370.391**-0.018 (0.174)(0.170)(0.037) Marital Status-0.2650.050-0.008 (0.167)(0.196)(0.036) Dependency (%house expenses)0.4830.4050.023 (0.317)(0.259)(0.045) Education0.0750.122**-0.006 (0.048)(0.056)(0.009) Time working at the bank0.003 -0.000 (0.004) (0.001) Observations256 255 (Pseudo) R-squared0.0270.0470.0060.0420.2430.256 Adj. R-squared0.2370.231 Number of clusters61 Robust standard errors are clustered at the branch level

21 Individual Rationality? Does program help loan officers to overcome procrastination problems or are they rationally responding to incentives? Incentives are very small relative to monthly pay Impact only manifests after branch managers get involved Impact lasts only for duration of intervention, vanishes once reminders and competition are removed Look at impact on general compensation of loan officers under existing incentive scheme, excluding program prizes

22 Impact on Individual Compensation Total Compensation (Salary + Bonus) Log (Total Compensation)Bonus (1)(2)(3)(4) (5) (6)(7) Sample is: Loan officers with compensation data for:Any period between June 08 and April 09 7 or more periods Any period between June 08 and April 09 Treatment (Nov-Apr)421,469***334,133*** (45,501)(43,650) Treatment (Nov-Jan)402,426***321,658***177,763***0.356***203,042*** (49,156)(49,577)(49,844)(0.0403)(37,066) Treatment (Feb-Apr)439,158***345,802***219,222***0.334***228,628*** (52,208)(48,566)(55,484)(0.0352)(45,954) Age Female3,3953,403 (3,557)(3,556) Marital Status95,553**95,494** (44,499)(44,460) Dependency-44,851-44,829 (40,699)(40,690) Education (years)75,40475,451 (61,213)(61,195) Time working at the bank19,086*19,093* (11,253)(11,252) Observations4,7164,7014,7164,7014,3204,7164,951 R-squared0.2580.3630.2580.3630.2840.2480.293 Adj. R-squared0.2470.3520.2470.3520.2720.2370.282 Number of clusters61 Specifications include branch and month fixed effects. Robust standard errors are clustered at the branch level

23 Conclusions Intervention was effective in shifting behavior of loan officers within month to desired allocation – No effects on total monthly productivity or loan quality Significantly increased well being – Increased job satisfaction and reduced stress levles – Improved planning behavior and managing monthly tasks – Increased compensation and bonuses Positive effects of the program are materialized only after branch managers were included – Seem to work mainly through encouragement, reminders and recognition, incentives alone are no sufficient to fight procrastination


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