All Questions
Tagged with bias consistency
25
questions
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66
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Bias vs consistency in instrumental variable estimation
So in Mostly Harmless Econometrics, page 154, they analyse the bias of instrumental variables:
They consider the case of one endogenous variable $x$, multiple instruments $Z$, and $\eta$ is the ...
- 231
1
vote
1
answer
119
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Difference between consistent and unbiased estimator [duplicate]
I have a problem where I have to think of an example to explain a practical example of consistency and unbiased. The example I thought of is the sample mean.
Consistency is when the estimator (sample ...
1
vote
1
answer
463
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Find the expectation of an exponential distribution estimator
So we've got a sample data coming from exponential distribution with parameter $\lambda$, and we take an estimator $\lambda_n = \frac{n}{X_1+X_2+\cdots+X_n}$.
I need to show that this is a biased and ...
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11
votes
4
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1k
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Is it true that an estimator will always asymptotically be consistent if it is biased in finite samples?
Is it true that an estimator will always asymptotically be consistent if it is biased in finite samples?
I feel like it is true but not sure exactly how to prove that...
- 119
3
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1
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3k
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Can bias of an estimate be decreased by increasing sample size?
I understand that in case of consistent estimates, larger the sample size, there's a higher probability that the estimate converges to true value of parameter. Now, using the sufficient condition of ...
- 1,387
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1
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413
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Consistency of ADL/ARDL/ARIMAX coefficients
Enders in Applied Econometric Time Series (4th edition, p.282) has following statement about consistency of coefficients in ARDL models:
"For the coefficients of C(L) to be unbiased estimates of the ...
1
vote
1
answer
253
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Show that bias term involving an indicator function convergences to zero
Assume that we have $N$ observations of i.i.d. data $(Y_i,X_i)_{i=1}^{N}$. We want to learn the model given by $Y=f(X)+\epsilon$. We use the data to estimate $\hat{f}$ using any machine learning ...
- 115
1
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0
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198
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Estimator, Bias and asymptotic distribution
I have a model;
$$y_i = \beta_1 + \frac{1}{\beta_2}x_i+\epsilon_i$$
To simplify I use OLS to regress on;
$$y_i = \delta_1 + \delta_2 x_1 + \epsilon_i$$
Thus I obtain the two estimators $\hat{\...
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2
votes
0
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959
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Lagged dependent variables, bias and consistency
I am working through Christopher Dougherty's Introduction to Econometrics, and am struggling to fully grasp the consequences of lagged dependent variables in terms of bias and consistency.
The key ...
- 71
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votes
1
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104
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Can any unbiased estimator be changed into a consistent estimator when estimating functions of the mean [closed]
For an i.i.d sequence of Random Variables $X_1, \dots, X_n$, each with mean $\mu = \mathbb E[X]$, the goal is to estimate some continuous function $f$ evaluated at the mean, $f[\mathbb E[X]]$.
If ...
- 123
1
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0
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250
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Are Poisson Regressions with Serial Correlation Biased or Inconsistent? (No Fixed Effects)
Let's say I've got panel data where a count outcome $y$ and continuous independent variable $x$ observed each time period $t=(1,2,...T)$ for each individual $i$. I am interested in how $x_{it}$ ...
- 189
2
votes
1
answer
571
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Bayesian analysis of multilevel model with lagged dependent variable
Currently, I am constructed a bayesian multilevel model to analyze a panel data set which now basically looks like the following: $y_{ijt} = \beta_{0ij} + X\beta + \epsilon_{ijt}$. So, now only a ...
- 43
1
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0
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34
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Unbiasedness and consistency
Assume the simple regression model satisfying all Gauss-Markov assumptions.
Somebody suggests the estimator
Why may someone consider such an estimator?
Why will this estimator be consistent? Why ...
- 11
5
votes
1
answer
1k
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Consistency and rates of convergence
Suppose that I have two statistics that are known to be consistent , e.g :
$ S_{n} ^2 $ (biased sample variance about sample mean) and $ S_{n-1}^2$ (bessel-corrected sample variance, that is unbiased)....
- 437
12
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2
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6k
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Why does unbiasedness not imply consistency
I'm reading deep learning by Ian Goodfellow et al. It introduces bias as
$$Bias(\theta)=E(\hat\theta)-\theta$$
where $\hat\theta$ and $\theta$ are the estimated parameter and the underlying real ...
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