Markov Chain Monte Carlo and the Application to Geodetic Time Series Analysis

The time evolution of geophysical phenomena can be characterised by stochastic time series. The stochastic nature of the signal stems from the geophysical phenomena involved and any noise, which may be due to, e.g., un-modelled effects or measurement errors. Until the 1990's, it was usually assumed that white noise could fully characterise this noise. However, this was demonstrated to be not the case and it was proven that this assumption leads to underestimated uncertainties of the geophysical parameters inferred from the geodetic time series. Therefore, in order to fully quantify all the uncertainties as robustly as possible, it is imperative to estimate not only the deterministic but also the stochastic parameters of the time series. In this regard, the Markov Chain Monte Carlo (MCMC) method can provide a sample of the distribution function of all parameters, including those regarding the noise, e.g., spectral index and amplitudes. After presenting the MCMC method and its implementation in our MCMC software we apply it to synthetic and real time series and perform a cross-evaluation using Maximum Likelihood Estimation (MLE) as implemented in the CATS software. Several examples as to how the MCMC method performs as a parameter estimation method for geodetic time series are given in this chapter. These include the applications to GPS position time series, superconducting gravity time series and monthly mean sea level (MSL) records, which all show very different stochastic properties. The impact of the estimated parameter uncertainties on sub-sequentially derived products is briefly demonstrated for the case of plate motion models. Finally, the MCMC results for weekly downsampled versions of the benchmark synthetic GNSS time series as provided in Chapter 2 are presented separately in an appendix

Tradition and Change in Marriage Payments in Vietnam, 1963-2000

Trends and determinants of marriage payments have rarely been examined at the population level despite their plausible implications for the welfare of family and the distribution of wealth across families and generations. In this study, we analyze population-based data from the Vietnam Study of Family Change to document prevalence and directions of marriage payments in Vietnam from 1963 to 2000. We investigate the extent to which structural and policy transformations (particularly market reform and the socialist policy that banned brideprice) influenced the practice of marriage payments as well as estimate how societal changes indirectly impacted payments via their effects on population characteristics. Results indicate that marriage payments surged following market reform but also reveal more nuanced trends and regional differences during earlier years. While the socialist attempts to eradicate brideprice appear to have been moderately successful in the North prior to economic renovation the evidence suggests they were largely unsuccessful in the South. Results suggest that structural and policy change explained most of the observed variations in marriage payments and that changing characteristics of the individuals who married mattered relatively little. We interpret the reemergence of marriage payments as attesting to resilience of traditional values and the unraveling of the socialist agenda, especially in the North, but also as a reflection of economic prosperity associated with market reform

Gender Imbalance: The Male/Female Sex Ratio Determination

sex ratio at birth, fertility, rational choice, tragedy of the commons, optimal sex ratio, D10, D71, J10, J13, J18,