Choosing summary statistics by least angle regression for approximate Bayesian computation

Bayesian statistical inference relies on the posterior distribution. Depending on the model, the posterior can be more or less difficult to derive. In recent years, there has been a lot of interest in complex settings where the likelihood is analytically intractable. In such situations, approximate Bayesian computation (ABC) provides an attractive way of carrying out Bayesian inference. For obtaining reliable posterior estimates however, it is important to keep the approximation errors small in ABC. The choice of an appropriate set of summary statistics plays a crucial role in this effort. Here, we report the development of a new algorithm that is based on least angle regression for choosing summary statistics. In two population genetic examples, the performance of the new algorithm is better than a previously proposed approach that uses partial least squares.     

Circular First- and Second-Order Balanced Repeated Measurements Designs

Sharma (1977 Sharma , V. K. ( 1977 ). Change-over designs with complete balance for first and second order residual effect . Canad. J. Statist. 5 : 121 – 132 .[Crossref] , [Google Scholar]) and Aggarwal et al. (2006 Aggarwal , M. L. , Deng , L.-Y. , Jha , M. K. ( 2006 ). Balanced residual treatment effects designs of first and second order . Statist. Probab. Lett. 76 : 597 – 600 .[Crossref], [Web of Science ®] , [Google Scholar]) considered non circular construction of first- and second-order balanced repeated measurements designs. Sharma et al. (2002 Sharma , V. K. , Varghese , C. , Jaggi , S. ( 2002 ). On optimality of change-over designs balanced for first and second order residual effects . Metron 60 : 153 – 162 . [Google Scholar]) constructed circular first- and second-order balanced repeated measurements designs only for a class with parameters (v, p = 3n, n = v ²) and also showed its universal optimality. In this article, we consider circular construction of first- and second-order balanced repeated measurements designs and strongly balanced repeated measurements designs by using the method of cyclic shifts. Some new circular designs with parameters (v, p, n) for cases p = v, p < v and p > v are given.     

Generalized neighbor designs with block size 3

A generalized neighbor design relaxes the equality condition on the number of times two treatments as neighbors in the design. In this article, we have considered the construction of some classes of generalized neighbor designs with block size k=3 by using the method of cyclic shifts. The distinguishing feature of this construction method is that the properties of a design can easily be obtained from the sets of shifts instead of constructing the actual blocks of the design. A catalog of generalized neighbor designs with block size k=3 is compiled for v∈{5,6,…,18} treatments and for different replications. We provide the reader with a simpler method of construction, and in general the catalog that gives an open choice to the experimenter for selecting any class of neighbor designs.     

Uncovering CSR meaning networks: A cross-national comparison of Turkey and Slovenia

This study addressed an important question about the meaning of corporate social responsibility (CSR), and how it is measured. Based on a comparison of the meaning networks of CSR in two countries with fundamentally different cultural and socioeconomic backgrounds, we argue that there is a need for an institutional perspective when studying CSR associations and expectations in a particular society. Thus empirical study involved the use of three methods the word-association technique, social network analysis, and blockmodeling using Pajek software; to provide deep insight into the structure of CSR associations. The findings suggest that the two societies have diverse collective cognitive structures regarding CSR. In Turkey, the philanthropic understanding of CSR is highly dominant, while the Slovenian social meaning of CSR is multidimensional. The findings point to the social construction of the concept of CSR with implications both for academic research and practice.     

Monetary Policy Announcements and Stock Returns: Evidence from the Pakistani Market

Objective of this paper is to analyze the impact of monetary policy announcements on stock returns. Event window of 31 days and an estimation window of 250 days was constructed. ARIMA model is applied to calculate the estimated returns from estimation window (t ? 250). Abnormal returns were calculated by taking the difference between actual and estimated returns. Then abnormal returns were aggregated as cumulative abnormal returns (CAR). CAR at 30% showed an impact of monetary policy announcements on stock returns. Null hypothesis of zero abnormal returns was rejected since the results were found in critical region under normal distribution. Further, we decomposed the interest rate into expected and un-expected to analyze their impact on stock returns. After checking for stationarity, Engle–Granger co-integration test were applied to check long run relationship between interest rates and stock return. A significant effect of interest rates (expected and un-expected) was observed in the short run. These results are in line with Kuttner’s (J Monet Econ 47:523–544, 2001), Bernanke and Kuttner’s (J Financ 60:1221–1257, 2005), Bredin et al.’s (US stock returns the impact of domestic monetary policy shocks, http://www.ucd.ie/t4cms/wp0604.pdf, 2007) and Ehrmann and Fratzscher’s (Equal size, equal role? Interest rate interdependence between the Euro Area and the United States, European Central Bank Working Paper 342, 2004). The study finds evidence of LR relationship between un-expected interest rates and whereas expected interest rates and stock returns have short term relationship.     

Estimation of finite population variance in successive sampling using multi-auxiliary variables

ABSTRACT

In this paper, a general class of estimators for estimating the finite population variance in successive sampling on two occasions using multi-auxiliary variables has been proposed. The expression of variance has also been derived. Further, it has been shown that the proposed general class of estimators is more efficient than the usual variance estimator and the class of variance estimators proposed by Singh et al. (2011) when we used more than one auxiliary variable. In addition, we support this with the aid of numerical illustration.     

Does gold act as a safe haven against exchange rate fluctuations? The case of Pakistan rupee

Investors often look for a refuge to avoid undesirable exposures to risk during period of extreme downturns in currency returns. We investigate daily gold and rupee exchange rates depreciation against set of currencies over the period of 1992–2015. Using wavelets at multiple time horizons; we find that gold act as a consistent short run hedge against exchange rate hence validating the exchange rate destruction hypothesis. This finding is helpful for speculators in their decision making while taking long and short positions accordingly. This finding suggests that central bank also need to keep other safe haven assets in reserves because the hedging ability of gold is only limited to short run. Further, the role of gold in providing protection against currency risks is also confirmed using quantile regression. These results assist portfolio managers and governments in formulating effectual diversification strategy for preserving investment portfolio during extreme event condition. Our results also suggest that gold has a lead relationship with exchange rate; however, this relationship switches over specific time intervals. This finding is of major concern for policy makers in determining the extent of stabilization in gold prices to bring consistency to exchange rate. Finally, the Granger coherence coefficients confirm that the strength of the causal relationship varies across over all frequencies. These conclusions have important implications for policy makers, economic analysts, portfolio managers and institutional investors.     

Canopy precipitation interception in urban forests in relation to stand structure

Urban forests provide important ecosystem services. In terms of hydrological benefits, forest ecosystems in urban environments represent qualitative and quantitative filter for rainwater. We quantified the canopy interception in relation to urban forest stand structure and rainfall intensity in an urban transect of the mixed (upland) forest in the city centre, towards a riparian pine forest and a floodplain hardwood forest in the City of Ljubljana, Slovenia. Bulk precipitation in open areas and throughfall were measured with fixed rainfall collectors in each forest. Stemflow was estimated from a review of relevant literature. We found that canopy interception in selected urban forests was mainly affected by tree species composition and other stand structure variables, such as canopy cover and tree dimensions. Average annual canopy interception was highest in the mixed forest (18.0% of bulk precipitation), while the riparian pine forest had the lowest level (3.9% of bulk precipitation) and the floodplain hardwood forest had the intermediate level for interception (7.1% of bulk precipitation). The mixed forest exhibited the stand structure factors that contributed to the highest canopy interception among the studied forests: high assemblage of dominant coniferous trees, denser canopy cover and the highest growing stock. Furthermore, rainfall intensity has proven to be an important factor for the seasonal partitioning (comparing the leafed and leafless period) of canopy interception. A better understanding of precipitation interception processes in urban forests is needed to assist urban forest managing and planning, aiming at maximizing canopy interception for the mitigation of stormwater runoff and flooding in urbanized watershed.