  We develop a Bayesian spatio-temporal model to study pre-industrial grain
market integration during the Finnish famine of the 1860s. Our model takes into
account several problematic features often present when analysing multiple
spatially interdependent time series. For example, compared with the error
correction methodology commonly applied in econometrics, our approach allows
simultaneous modelling of multiple interdependent time series avoiding
cumbersome statistical testing needed to predetermine the market leader as a
point of reference. Furthermore, introducing a flexible spatio-temporal
structure enables analysing detailed regional and temporal dynamics of the
market mechanisms. Applying the proposed method, we detected spatially
asymmetric "price ripples" that spread out from the shock origin. We
corroborated the existing literature on the speedier adjustment to emerging
price differentials during the famine, but we observed this principally in
urban markets. This hastened return to long-run equilibrium means faster and
longer travel of price shocks, implying prolonged out-of-equilibrium dynamics,
proliferated influence of market shocks, and, importantly, a wider spread of
famine conditions.
