### Table 1. Upper and Lower Horizon Trees Upper Horizon tree Lower Horizon tree

### Table 1: Cost from initial condition [3; ?2]

"... In PAGE 5: ...cheme (as described in Section 4.). The erratic behav- ior demonstrated by the receding horizon controllers was tamed and drastically improved performance achieved for each of the tested horizons. Table1 summaries the costs accumulated for each of the horizons T = 0:2; 0:3; 0:5 and 1:0. A surprising result is that even a short horizon dramatically reduces the cost over that of Sontag apos;s for- mula alone, demonstrating the power of the combination of CLF techniques with even a minimal amount of on-line computation.... ..."

### Table 3 Model parameters

1999

Cited by 97

### Table 1 Average estimation and measurement errors for various initial conditions, based on 20 Monte Carlo simulations for each set of initial conditions

2003

"... In PAGE 10: ... The control u[k] that was used was based on the fuzzy infinite horizon optimal control described in [31]. Table1 shows the average estimation error and measurement error that resulted with various initial conditions. It can be seen that the fuzzy Kalman filter improved the state estimate by a significant amount for all of the initial conditions that were considered.... ..."

### Table 6: Degree of Naivete Required for Procrastination (Principal G01 $10,000, Horizon G01 30 years, G05G05G06G07 G01 G08G05G09) Never transfer funds if

1999

"... In PAGE 17: ... All that is required is that the person be merely naive enough to believe her future tolerance for delay will be at least one day smaller than her true tolerance for delay. Table6 reports the degree of naivete required to induce a person to never make the transfer for various G09G04, G09G05,and . Table 6 assumes a principal of $10,000, a 30-year investment horizon, and a yearly discount factor of G05G06G07 .... In PAGE 17: ... Table 6 reports the degree of naivete required to induce a person to never make the transfer for various G09G04, G09G05,and . Table6 assumes a principal of $10,000, a 30-year investment horizon, and a yearly discount factor of G05G06G07 . Importantly, the conditions in the table are sufficient to guarantee severe procrastination, but they are not necessary.... In PAGE 17: ... See the Appendix for a derivation of these conditions. Table6 reveals that in general need not be that much larger than to induce severe procrastination.17 G01G06 Note that a sophisticate might follow any plan that completes the task within 12 days and has 12-day cycles.... In PAGE 30: ...Table6 : Let G01 denote the delay perceived in period by a person with perceptions . To formalize a solution concept for partial naivete, we assume that G01 is equal to the delay perceived in period by a completely sophisticated person with self-control problem (which can be uniquely determined via backwards induction).... ..."

Cited by 4

### Table 2: Descriptive statistics by financial planning horizon

2006

"... In PAGE 12: ... I use IVEware imputation and variance estimation software, which follows a sequential regression imputation method described in Ragunathan, Lepkowski, van Hoewyk, and Solenberger (2001). Table2 shows descriptive statistics by financial planning horizon. The average growth rates of consumption vary widely from -12% for persons with a short financial planning horizon to 3.... ..."

### Table 1. Performance of joint indicators at different horizons

"... In PAGE 5: ...combination appears to be a threshold for a credit gap of 4 percentage points and an asset prices gap of 40 % and an investment gap of zero. Table1 reports the performance of joint indicator at different horizons. Table 1.... ..."

### Table 7. Decision rule assessment. Performance of the hybrid forecast of Industrial production. Horizon = 1 month Horizon = 6 months Horizon = 12 months

2003

"... In PAGE 23: ... We evaluate the performance of the hybrid forecast and contrast it to that of the forecasts in the pair by (1) comparing the MSE of the hybrid forecast to the MSE of the individual forecasts; and (2) testing optimality of each forecast for quadratic loss. The entries in Table7 equal 1 if the MSE of the switching forecast is less than or equal to both the MSEs of the individual forecasts. The table reveals that in 26 out of 30 cases the switching forecast is at least as accurate as the individual forecasts.... ..."

Cited by 3

### Table 2 The optimal horizon in three benchmark cases

"... In PAGE 18: ...05) on price level stability is included. Table2 and Graph 2 summarise the results in each of these cases. Graph 2 plots the losses as a function of the horizon.... In PAGE 20: ... This is particularly the case when there is some, be it small, weight on interest rate stabilisation in the loss function. As shown in the middle panel of Table2 , in both cases a very similar stabilisation of the output gap and inflation is achieved, but a price level objective is rather more beneficial in terms of the interest rate volatility it creates. The standard deviation of the nominal interest rate under an optimal price level objective is 75 basis points lower than under an optimal inflation objective.... In PAGE 20: ... These results also confirm the analysis in Reifschneider and Williams (1999) and Wolman (1998) who show that when agents are forward-looking and the central bank credibly responds to deviations of the price level from some target, problems associated with the lower zero bound on interest rates and possible risks of deflationary spirals may become less important. Fourth, the lower panel of Table2 and Graph 2 show that with even a small weight on price level volatility the balance is completely tilted in favour of an appropriately defined price level objective. Obviously, a forward-looking inflation objective results in price level drift.... ..."