Are there any corruption cases in New Jersey?

Everyone knows that in New Jersey, we have the best government that money can buy. But even after a 2016 U.S. Supreme Court decision that dramatically raised the bar for proving federal bribery and political corruption, New Jersey public officials still find creative ways to get caught with their hands in the till.

Who was the Bloomfield NJ councilman guilty of bribery?

Bloomfield councilman Elias Chalet, 56, admitted to second-degree bribery in official or political matters for accepting $15,000 in bribes from a local businessman to ensure the town bought one of the man’s commercial properties.

Who are the NJ Public Workers guilty of?

Lamont King, 41 of Trenton, pleaded guilty in Superior Court in Mercer County July to a second-degree charge of conspiracy to commit a pattern of official misconduct. Using his position as a family services worker, he pressured two women he was responsible for supervising in court-ordered child visits into having sex with him, authorities said.

What is the impact of corruption on development?

In addition, reducing corruption is at the heart of the Sustainable Development Goals and achieving the ambitious targets set for Financing for Development. Corruption has a disproportionate impact on the poor and most vulnerable, increasing costs and reducing access to services, including health, education and justice.

Where does the data for corruption come from?

The data comes from the Global Corruption Barometer, produced by Transparency International, and the public services in question are: education; judiciary; medical and health; police; registry and permit services; utilities; tax revenue and/or customs; and land services. Once again, cross-country heterogeneity stands out.

How is corruption a regressive tax on the poor?

In fact, petty corruption in the form of bribes often acts as a regressive tax, since the burden typically falls disproportionately on the poor. This visualization, taken from the World Development Report (2011), uses data from Ecuador to estimate the cost of bribes paid relative to income.