A Robust InSAR Phase Unwrapping Method via Phase Gradient Estimation Network

Phase unwrapping is a critical step in synthetic aperture radar interferometry (InSAR) data processing chains. In almost all phase unwrapping methods, estimating the phase gradient according to the phase continuity assumption (PGE-PCA) is an essential step. The phase continuity assumption is not always satisfied due to the presence of noise and abrupt terrain changes; therefore, it is difficult to get the correct phase gradient. In this paper, we propose a robust least squares phase unwrapping method that works via a phase gradient estimation network based on the encoder–decoder architecture (PGENet) for InSAR. In this method, from a large number of wrapped phase images with topography features and different levels of noise, the deep convolutional neural network can learn global phase features and the phase gradient between adjacent pixels, so a more accurate and robust phase gradient can be predicted than that obtained by PGE-PCA. To get the phase unwrapping result, we use the traditional least squares solver to minimize the difference between the gradient obtained by PGENet and the gradient of the unwrapped phase. Experiments on simulated and real InSAR data demonstrated that the proposed method outperforms the other five well-established phase unwrapping methods and is robust to noise.

Trends and determinants of raising ECBs in Indian Context

This study examines the effect of capital control measures initiated during the last two decades in terms of all-in-cost ceilings and enhanced limits on ECB in India over the sample period 2004Q1 to 2020Q2. Using global liquidity, the exchange rate between INR/USD, imports and interest rate differentials as control variables and changes in capital control measures from 2008 to 2011 in the all-in-cost ceiling, and changes in the enhanced limits on ECBs from USD 500 million to USD 750 million under the automatic route in 2012, regression analysis of three ECB series show interesting results. Using Robust Least Squares method, we document that (1) the successive increment in all-in-cost ceilings on ECB from 2008 to 2011 is inducing ECBs to flow, indicating that Indian firms benefit more than they pay due to increase the cost for ECBs having maturities 3<5 years. However, such capital control measures are not effective on ECBs having maturities >5 years. (2) The effect of the enhanced limits on ECBs from USD 500 million to USD 750 million under the automatic route in 2012 has a pronounced impact on ECB, averaging 1602.1 USD million per quarter. We observed that CCAs in India are initiated in response to the volatility of the exchange rate and global liquidity, imports, and interest rate differentials are significant variables in India's required capital control actions.

Impact of Economic and Noneconomic Factors on Inflow of Remittances into Bangladesh

Purpose: Remittance plays an important role in the economy of Bangladesh. It also contributes to the change in the social structure and standard of living. The purpose of the study is to identify the economic and non-economic determinants of the remittance inflow into Bangladesh. Methodology: The study considered two types of variables as the determinants of the remittance inflow: economic and non-economic. Economic determinants of remittances inflows included exchange rate, education, economic growth rate, and market interest rate. The non-economic determinants covered control of corruption, government effectiveness, and political stability. Monthly data were used for the case of economic determinants from 2014 to 2020 and annual data were used in the case of non-economic determinants from 1996 to 2018. The marginal effect of each variable has been analyzed by using the Robust Least Squares (RLS) method. Results: The estimated results of this study state that, economic determinants like capital formation and education factors have a positive and significant impact on remittances inflows in both static and dynamic cases. However, the exchange rate does not create a positive impact due to volatility. The RLS estimation shows the control of corruption has a positive impact on remittances inflows whereas government effectiveness and political stability hurt remittances inflows in Bangladesh. Implications: The current study identified the significant determinates of remittances inflows in Bangladesh. The findings have implications for policy formulation as regard remittances and non-resident Bangladeshis.

Profit shifting in Brazil and the impact of tax havens

ABSTRACT We investigate tax-induced profit shifting in Brazil and the impact of tax havens on the shifting behavior of firms. Profit shifting research in Brazil is virtually non-existent, although the shifting incentives in Brazil are prominent. Our research fills this gap with evidences in the novel Brazilian context. Profit shifting is a tax-minimization strategy where multinational enterprises perform intra-firm transactions to allocate taxable profits to low-tax locations. Brazil combines a remarking set of profit shifting incentives, especially a high corporate tax rate, extremely complex tax system, and distinguished transfer pricing rules. Further researches may leverage from the shifting incentives in Brazil, since it provides opportunities to investigate additional factors that affect the shifting behavior of firms. We analyze 989 transaction-by-country observations for the period of 2010-2017. Baseline analysis follows the robust least squares approach with controlling covariates. Linear estimate model derives from the conventional Cobb-Douglas production function, to analyze the impact of shifting incentives on profit maximization. We find that Brazilian firms have a high level of intra-firm transactions with related parties located in low-tax countries, especially with tax havens. It represents a strong evidence of profit shifting behavior in Brazilian firms.

Combined Constrained Robust Least Squares Approach and Block-Pulse Functions Technique for Tracking Control Synthesis of Uncertain Bilinear Systems with Multiple Time-Delayed States under Bounded Input Control

The present study tackles the tracking control problem for unstructured uncertain bilinear systems with multiple time-delayed states subject to control input constraints. First, a new method is introduced to design memory state feedback controllers with compensator gain based on the use of operational properties of block-pulse functions basis. The proposed technique permits transformation of the posed control problem into a constrained and robust optimization problem. The constrained robust least squares approach is then used for determination of the control gains. Second, new sufficient conditions are proposed for the practical stability analysis of the closed-loop system, where a domain of attraction is estimated. A real-world example, the headbox control of a paper machine, demonstrates the efficiency of the proposed method.