Compact canonical quantization on the light cone (DLCQ) is examined in the limit of infinite periodicity lenth L. Pauli Jordan commutators are found to approach continuum expressions with marginal non causal terms of order L −3/4 traced back to the handling of IR divergence through the elimination of zero modes. In contrast direct quantization in the continuum (CLCQ) in terms of field operators...

We propose simulation-based forecasting methods for the noncausal vector autoregressive model proposed by Lanne and Saikkonen (2012). Simulation or numerical methods are required because the prediction problem is generally nonlinear and, therefore, its analytical solution is not available. It turns out that different special cases of the model call for different simulation procedures. Simulatio...

Bellʼs theorem in physics, as well as causal discovery in machine learning, both face the problem of deciding whether observed data is compatible with a presumed causal relationship between the variables (for example, a local hidden variable model). Traditionally, Bell inequalities have been used to describe the restrictions imposed by causal structures on marginal distributions. However, some ...

With the development of deregulated power systems and increase of prices in some hours of day and increase fuel price, demand response programs were noticed more by customers. demand response consists of a series of activities that governments or utilities design to change the amount or time of electric energy consumption, to achieve better social welfare or some times for maximizing the benefi...

We investigate the problem of estimating the causal effect of a treatment on individual subjects from observational data; this is a central problem in various application domains, including healthcare, social sciences, and online advertising. Within the Neyman-Rubin potential outcomes model, we use the Kullback-Leibler (KL) divergence between the estimated and true distributions as a measure of...

Given causal graph assumptions, intervention-specific counterfactual distributions of the data can be defined by the so called G-computation formula, which is obtained by carrying out these interventions on the likelihood of the data factorized according to the causal graph. The obtained G-computation formula represents the counterfactual distribution the data would have had if this interventio...

This paper identifies the key causal factors behind farmers’ marketing decisions in Mozambique. A two-step decision making process is modelled. Farmers decide, first, whether or not to participate in the market and, second, how much to market. The model is estimated using a Heckman switching regression approach. Marginal effects are calculated for the poor and the nonpoor and broken down into a...

Increased education affects market and non-market outcomes. This paper investigates the causal impact of extension compulsory from 6 to 9 years on females’ education, marriage, fertility outcomes in Thailand. Using data Multiple Indicator Cluster Survey (MICS) a donut-hole Regression Discontinuity (RD) design, we show that new law increases lower secondary school completion girls, leading decre...