November 3 – Informs Annual Meeting – Shape Constrained Kernel Weighted Least Squares for the Estimation of Production Functions


This paper proposes a unifying model and estimator we call Shape Constrained Kernel-weighted Least Squares (SCKLS). We show the relationship between the SCKLS estimator and both the Convex Nonparametric Least Squares (CNLS) and Du’s estimators. Specifically, the SCKLS estimator converges to the CNLS estimator as the bandwidth goes to zero. We compare the performance of the three estimators (SCKLS, CNLS, and Du’s estimator) via Monte Carlo simulations.

Workshop 2015 -Advances in DEA Theory and Applications

The Workshop 2015 -Advances in DEA Theory and Applications was held in Roppongi (Tokyo) Japan on December 1st and 2nd and hosted by Kaoru Tone and the Graduate Research Institute for Policy Studies (GRIPS – 政策研究大学院大学).

This two-day workshop included 13 paper on Data Envelopment Analysis (DEA) will provide the basis for Professor Tone’s new book “Advances in DEA Theory and Applications: with Examples in Forecasting Models”. It featured presentation by Hirofumi Fukuyama, Joe Paradi, Miki Tsutsui, and Kaoru Tone.

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Informs Annual Meeting – November 1-4


The Institute for Operations Research and the Management Sciences (INFORMS) is an international society for practitioners in the fields of operations research (OR) and management science. Informs held their annual meeting November 1-4 in Philadelphia, PA. The conference had more than 5,000 attendees and 1,000 sessions.

How inefficient are U.S. hospitals? What changes can lead to improvement?


We use U.S. hospital data from 2004 to 2011 to estimate a cost function using a Bayesisan semi-nonparametric method that allows for a heteroskedastic inefficiency. Moreover, we evaluate what is the impact of variables, such as region and hospital size, on cost estimating both the size and robustness of the variables in terms of reducing cost for hospitals.

Adaptively Partitioned Convex Nonparametric Least Squares


This research overcomes both the decreased accuracy of Convex Adaptive Partitioning on real production survey datasets and the cross-validation performance challenges of CNLS to create a robust and scalable adaptive partitioning-based convex regression method.

We discover that real production datasets often contain local monotonicity violations, which affect CAP’s ability to propose feasible basis region splits. Moreover, we note that CNLS’s error minimization strategy within the observed dataset results in poor estimations on unobserved firms due to over-fitting. We create a hybrid of both methods that preserves their most favorable properties at a small computational time expense. The paper summarizing this research is available on Arxiv.

Shape Constrained Kernel-weighted Least Squares (SCKLS)


SCKLS (shape constrained kernel-weighted least squares) estimator integrates kernel-weighting to convex nonparametric least squares.

Kernel regression is one of the powerful nonparametric estimation methods. By imposing more weight to some closer points, kernel regression helps to avoid over-fitting although it requires the tuning parameter, bandwidth. By imposing some shape constraints such as monotonicity and concavity, we propose SCKLS estimator and apply it to estimate production function with simulated and real data. We also investigate the relationship with Convex Nonparametric Least Squares (CNLS) and we found that CNLS is minimum bias estimator in the class of SCKLS estimator. This is on-going research with Daisuke Yagi. This is the first chapter of his dissertation.

September 24 – Penn State University: Production Economics for Performance Evaluation of Engineered Systems: The Example of Finnish Electricity Distribution

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The Finnish electricity market has a competitive energy generation market and a monopolistic transmission system. To regulate the local monopoly power of network operators, the government regulator uses frontier estimation methods. We describe the new regulatory system developed for the Finnish regulator, which is based on the method Stochastic semi-Nonparametric Envelopment of Data (StoNED) and utilizes panel data to detect the excessive costs from random noise.

October 3 and 4: College Industry Council on Material Handling Education Semi-annual Meeting in Jacksonville


The College Industry Council on Material Handling Education (CICMHE) is a group of 16 academic and 8 industry members that work to increase awareness, understanding, exploration, and development of material handling and logistics through projects and events.

CICMHE meet in Jacksonville as part of the MHI’s annual conference. The two-day event resulted in a set of projects MHI will fund to promote material handling and logistics education along with allowing considering progress on planning the upcoming events for CICMHE such as Promat.

Shape constrained Semi-nonparametric Stochastic Frontiers estimation using a local maximum likelihood approach


We propose a shape-constrained production function estimator starting from the method described in Kumbhakar, Park, Simar, Tsionas 2006 (KPST).

We maximize the loglikelihood of a local linear estimator at each observation. We estimate the parameters for the noise and inefficiency distributions that are potentially heteroscedasticity.

The challenge to imposing shape constraints, such as monotonicity and concavity, is we need to jointly esitmate the maximum likelihood function for all observations while imposing the constraints. This is on-going research with Kevin Layer.

Japan Project Meeting – July 30-31 Tokyo Japan



ADBI hosted the annual National Bureau of Economic Research (NBER) Japan Project conference, featuring cutting edge economic research on Japan. This year’s papers very much focused on microeconomics, with a number of studies using a “natural experiment” approach to analyze diverse phenomena, including firms’ decisions to use American-style or Japanese-style import procurement, women’s childbirth and employment decisions, and changes in risk assessment and the location of firms after the Great East Japan Earthquake in March 2011.