This paper investigates patterns in housing market networks using Australian and Chinese data and a novel econometric approach based on pairwise time-varying Granger causality tests. The focus is on four fundamental questions. (1) Have housing markets become increasingly connected over time? (2) Does housing market connectivity increase or decrease with house prices? (3) Are socio-economic and geographic proximity important for housing market connections? (4) Do economic fundamentals or sentiment drive connectivity? The results reveal interesting differences in these markets and suggest that one size is not likely to fit all in terms of housing market policy.

This paper explores implications of weak identification in common ‘long memory’ and recent ‘rough’ approaches to modeling volatility dynamics of financial assets. We unveil an asymptotic near-observational equivalence between a long memory model with weak autoregressive dynamics and a rough model with a near-unit autoregressive root. Standard methods struggle to distinguish them, and conventional asymptotics are invalid. We propose an identification-robust approach to construct confidence sets that reveal the uncertainty and aid inference. Empirical studies based on realized volatility and trading volume often fail to statistically reject either model, thereby providing evidence of their potential coexistence.