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systematic shocks to the ex - post returns(passive) caused byserial correlation
dramatic shocks to the system , which ripple along the timeline in the form of inflated or deflated error(passive) can be caused bySerial correlation
Import levels are also correlated across timeresultingin serial correlation
In the meantime , an individual 's repeated measurements may be a response to a time - varying , systematic processresultingin serial correlation
This situationcreatesserial correlation
the overlap in the five - year returns(passive) caused bythe serial correlation
concernedwould leadto serial correlation
an autocorrelated dependent variable(passive) would be caused byserial correlation
a decreased dwstatcontributingto serial correlation
when a trend does fall more than expectedresultsin serial correlation
biasresultingfrom serial correlation
educational measurement ... observation or self - reportingcreatesserial correlation
adding extra lags to the equationleadsto serial correlation
a stationary first - order choice process(passive) caused byserial correlation
the returns generated by the asset in the previously defined intervals(passive) get influenced byserial correlation
overlapping forecast horizons(passive) caused bythe serial correlation
Memory and emotioncreateserial correlation
errorsresultingfrom serial correlation
All of these factorscould resultin serial correlation
misspecification of the functional form(passive) can also be caused bySerial correlation
efficiency of(passive) caused byserial correlation
First , when a mainshock occurs , it provokes many aftershocksthus creatingserial correlation
fixed effectscauseserial correlation
problems for model fitting and statisticscauseproblems for model fitting and statistics
from using the monthly dataresultsfrom using the monthly data
in quadrats that are closer together are more correlatedresultsin quadrats that are closer together are more correlated
to incorrect inferences being made from samplesleadsto incorrect inferences being made from samples
from a poor choice of parameters in a linear congruential random number generatorresultsfrom a poor choice of parameters in a linear congruential random number generator
a biased forecast ... and that bias in turn is correlated with the forecast origincreatesa biased forecast ... and that bias in turn is correlated with the forecast origin
asset bubblescausesasset bubbles
the standard errors of the coefficients to be smaller than they actually are and higher R - squaredcausesthe standard errors of the coefficients to be smaller than they actually are and higher R - squared
the time series to drift and over a short period of timecausesthe time series to drift and over a short period of time
the estimated variances of the regression coefficients to be biasedcausesthe estimated variances of the regression coefficients to be biased
to unreliable statistical significance of trend57,58could leadto unreliable statistical significance of trend57,58
to multicollinearitywould leadto multicollinearity
investment opportunities for patient long - term investorscreatesinvestment opportunities for patient long - term investors
a technical violation of an OLS assumptioncausesa technical violation of an OLS assumption
in ‘ smooth ’ returns , volatility masks the true extent of tail losses8resultingin ‘ smooth ’ returns , volatility masks the true extent of tail losses8
the variability(passive) caused bythe variability
T - statistics to be larger than they actually are , and thus P - values to be smaller than they actually arecan causeT - statistics to be larger than they actually are , and thus P - values to be smaller than they actually are
in an underestimate of the standard error in a statistical model , which then can cause variables to appear to be statistically significant when they are in fact notcan resultin an underestimate of the standard error in a statistical model , which then can cause variables to appear to be statistically significant when they are in fact not
infinite variance(passive) caused byinfinite variance
in estimates of the regression coefficients which are asymptotically efficientresultingin estimates of the regression coefficients which are asymptotically efficient
to biased resultsleadsto biased results
from unobserved factors affecting the outcomesresultingfrom unobserved factors affecting the outcomes
in the ordinary least squares method or due to another factordiscoveredin the ordinary least squares method or due to another factor
to overestimates of their reliabilitymay have ledto overestimates of their reliability
in co - integrationresultingin co - integration
trend detection(passive) caused bytrend detection
from the imperfect appraisalsresultsfrom the imperfect appraisals
Difficulties(passive) caused byDifficulties
to underestimating the variance of difference - in - difference estimates when many time steps are used [ 15 ] ( § 4Ccan leadto underestimating the variance of difference - in - difference estimates when many time steps are used [ 15 ] ( § 4C
due to lagged variablesmay resultdue to lagged variables
the deviation(passive) caused bythe deviation
OLS to no longer be a minimum variance estimatorcausesOLS to no longer be a minimum variance estimator
albatross habitat models(passive) were influenced byalbatross habitat models