Stochastic Limit Theory: An Introduction for Econometricians

By James Davidson. 1994

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Citations in the corpus

Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning (2019, background): “More speciﬁcally, ﬁrst, we have α n φ n (Davidson, 1994, Chapter 13).”
LONG MEMORY TESTING IN THE TIME DOMAIN (2007, background): “It also follows with slight modifications that p T ˆs(b ), with ˆ s(b ) defined in ( 9 ), has a proper”
Estimation of Panel Group Structure Models with Structural Breaks in Group Memberships and Coefficients (2020, unknown): “Here we use the observation that an Lr-bounded mixing sequence is an Lp mixingale sequence for 1 ≤ p r as discussed in (Davidson, 1994, page 248).”
Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model (2004, background): “The NED measure of memory is unavailable without first moments, but an alternative is provided by Pötscher and Prucha’s (1991) notion of L0-approximability (see also Davidson (1994) Chapter 17.”
Inference in Autoregression under Heteroskedasticity (2006, unknown): “By Theorem 17.10 in Davidson (1994), for 1 h p, fYt h lg is also mean-zero L2-NED on futg, and necessarily an L1-mixingale.”
Inference in VARs with Conditional Heteroskedasticity of Unknown Form (2016, background): “Furthermore, Assump- tion 2.2(ii) together with Theorem 14.3 in Davidson (1994) imply that its α-mixing coefficients (αV,m(n), n ∈ N) decay at the same rate as (αu(n), n ∈ N) of the process (ut, t ∈ Z).”
Covariance matrix estimation and linear process bootstrap for multivariate time series of possibly increasing dimension (2015, background): “Assumption (A4) is, for instance, fulfilled if the underlying process is linear or α-mixing with summable mixing coefficients by Ibragimov’s inequality; cf., for example, Davidson (1994), Theorem 14.2.”
Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications (2010, unknown): “…condition is satisfied by each of functions f (·), W(·), and K(·); (v) The process (Xt,Yt) is strictly stationary and absolutely regular (see, e.g., Davidson 1994, p. 209) with mixing coefficients β(j) satisfying ∑∞ j=1 j2βδ/(1+δ)(j) < ∞, where δ is the same as in (ii); (vi) As n → ∞, h,h′ → 0…”
Are 'Nearly Exogenous' Instruments Reliable? (2008, background): “For any independent sequence Zi′ui, if E[Zi′ui]2+ δbΔb∞ for some δN0 for all i=1, 2, 3,…, N, then Liapunov's theorem leads to the limiting results in (c); see James Davidson (1994).”
Maximum likelihood estimation of a spatial autoregressive Tobit model (2015, unknown): “(Lemma 17.15 in Davidson (1994)) Let B and ρ be two non-negative random variables and assume ||ρ||q < ∞, ||B||p < ∞, and ||Bρ||r < ∞, for q−1 + p−1 = 1, q > 1 and r > 2.”