Taxes

WFP asks candidates to stop defending taxpayers

WFP asks candidates to stop defending taxpayers

Candidates seeking the endorsement of the Working Families Party in 2020 are being asked about their positions on a number of predictable topics, such as single-payer health care and an increase in the minimum wage. But a questionnaire from the party also includes an unexpected entry. In essence, the party asks would-be candidates if they are willing to stop talking about taxpayers and taxes.

“Messages that frame ‘taxpayers’ as an aggrieved or marginalized group promotes an anti-tax, anti-government worldview that is often used to justify disinvestment and austerity policies,” the question reads, according to a copy of the document obtained by POLITICO. “’Taxpayer’ has also become a racially coded term designed to appeal to white individuals and reinforce the misconception that they are paying taxes to support the needs of people (often implied to be non-white) who don’t pay taxes. Will you avoid messaging that centers ‘taxpayers’ or ‘tax burdens’ and instead talk about ‘public funding’ and the public as a whole?”

Total Property Tax Levies Rise Slightly In New York

Total Property Tax Levies Rise Slightly In New York

The total amount of money raised in property taxes by local governments increased by 2.4 percent this year to a total of $36.6 billion, according to a report released Tuesday by Comptroller Tom DiNapoli’s office.

The report found the majority of that revenue, nearly $23 billion, was levied by school districts.

County governments collected $6 billion in property tax levies, about 16 percent of property taxes in the state.

Property taxes in the state are capped at 2 percent or the rate of inflation, whichever is lower. Local governments can vote to override the cap, which has been in place since 2012.

New Yorkers pay some of the highest property taxes in the country and the highest as a percentage of home value. Still, the last decade has led to a slower growth of tax levies statewide.

The report found that from 2017 to 2019, property tax levies grew the most in cities, 6.1 percent. In towns, the levies grew 4.4 percent. School district leaves have grown an even 4 percent.

PHP Script for Converting RPTL 1590 Reports into Excel Files

Real Property Tax Law 1590 requires that municipalities post their tax rolls, within 10 days of the proposed and final rolls being approved. Below is an PHP script that will extract the reports into a CSV file for importing into Microsoft Excel or a GIS program. It extracts the text from the PDF using pdftotext from the poppler-util.

If you do not want to install poppler-util, I would encourage to check out the simpler and better maintained R Script for for Converting RPTL 1590 Reports that I also wrote. Both versions can also be found on my GitHub.

<?php

// this program requires pdftotext (a linux program) and PHP version 7.2

// first convert PDF to text
$pdfdir = "input-pdf";
$textdir = "output-txt";

// delete old input-text
if (isset($argv[1]) && $argv[1] == 'delete') {
	echo "Deleting old conversions ...\n";
	system("rm $textdir/*");
}

foreach (scandir($pdfdir) as $file) {
	if (substr($file, -4) !== '.pdf') {
		continue;
	}
	
	$textfile = substr($file, 0, -4).".txt";
	$town = substr($file, 0, -4);
	
	echo ("#### START $town #### \n");
	
	if (file_exists("$textdir/$textfile")) {
		echo "Text file exists, not converting PDF again (arg[1] == delete to override).\n";
	}
	else {
		echo "Converting to text file ...";
		system('pdftotext -layout '.escapeshellarg("$pdfdir/$file").' '.escapeshellarg("$textdir/$textfile"));
		echo " DONE\n";
	}
	
	$text = file("$textdir/$textfile");
	$town = substr($file, 0, -4);

	$taxroll = array();
	$payerId = 0;
	
	$output = "";
	
	$townId = "";
	$swisId = "";
	$countyId = "";
	$villageId = "";
	
	for ($i = 0; $i < count($text); $i++) {
		if ($i % 100 == 0) echo "#";
		
		// capture county - town - swis
		if (preg_match('/COUNTY\s*?- (.*?)\s{2}/', $text[$i], $matches)) $countyId = $matches[1];
		if (preg_match('/CITY\s*?- (.*?)\s{2}/', $text[$i], $matches)) $townId = $matches[1];
		if (preg_match('/TOWN\s*?- (.*?)\s{2}/', $text[$i], $matches)) $townId = $matches[1];
		if (preg_match('/VILLAGE\s*?- (.*?)\s{2}/', $text[$i], $matches)) $villageId = $matches[1];
		if (preg_match('/SWIS\s*?- (.*?)\s{2}/', $text[$i], $matches)) $swisId = $matches[1];

		
		// first line = tax id
		$pattern = '/\*{3,} ((\d|\-|\.){4,}) \*{3,}/';
		preg_match($pattern, $text[$i], $matches);

		// we've found the start of a new tax record!
		if (isset($matches[1])) {
			$i++;
			
			$taxpayer = array();
			$j = 0;
			// output each part onto the line
			while (isset($text[$i]) && !preg_match('/\*{3,}/', $text[$i])) {
				$split = preg_split('/\s{2,}/', $text[$i]);
				
				$taxpayer[$j] = $split;
				$i++; $j++;
			} 
			
			
			$taxpayer[$j] = array('location',$countyId, $townId, $villageId, $swisId);
						
			$taxroll[$payerId++] = $taxpayer;
			$i--;
		}
	}

	// export unprocess tax rolls for debug
	file_put_contents("output-debug/$town.txt", print_r($taxroll,true));
	
	// next scan for all special district types in file
	$specialDistType = array();
	
	foreach ($taxroll as $taxpayer) {
		for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					if (preg_match('/^([A-Z]{2})(\d\d\d) (.*?)( TO|$|\d{2,})/', $taxpayer[$i][$j],$matches)) {
						$specialDistType[$matches[1]] = $matches[1];						
					}
				}	
		}
	}
	ksort($specialDistType);

	// then process into a nice field
	$formTax = array();

	foreach ($taxroll as $taxpayer) {
		$formPayer = array();
		
		$formPayer[0] = $taxpayer[1][0]; // tax id
		
		if (isset($taxpayer[0][1]) && preg_match('/^(\d.*?) (.*?)$/',$taxpayer[0][1], $address)) {
			$formPayer[1] = $address[1]; // street number
			$formPayer[2] = ucwords(strtolower($address[2])); // street name
		}
		elseif (isset($taxpayer[0][1]))  {
			$formPayer[1] = '';
			$formPayer[2] = ucwords(strtolower($taxpayer[0][1])); // street name
		}
		
		if (isset($formPayer[1])) $formPayer[23] = ltrim($formPayer[1].' '.$formPayer[2]); // full street 
		else if (isset($formPayer[1])) $formPayer[23] = ltrim($formPayer[2]);
		
		$formPayer[3] = ucwords(strtolower($taxpayer[2][0])); // owner 1
		
		// next five lines are either are owner or address info
		for ($i = 3; $i < 8; $i++) {
			
			if (!isset($taxpayer[$i][0])) continue;
			
			// if a taxpayer name
			if (preg_match('/^[A-Z]/',$taxpayer[$i][0]) && !preg_match('/^PO/',$taxpayer[$i][0]) && !preg_match('/^(.*?), (\w\w) (.*?)$/',$taxpayer[$i][0])) 	{
				
				if (!isset($formPayer[4])) $formPayer[4] = ucwords(strtolower($taxpayer[$i][0]));
				else if (!isset($formPayer[5])) $formPayer[5] = ucwords(strtolower($taxpayer[$i][0]));
				else if (!isset($formPayer[6])) $formPayer[6] = ucwords(strtolower($taxpayer[$i][0]));
			}
			
			// if a city - state - zip
			else if (preg_match('/^(.*?), (\w\w) (.*?)$/',$taxpayer[$i][0], $address)) {
				$formPayer[10] = ucwords(strtolower($address[1]));
				$formPayer[11] = strtoupper($address[2]);
				$formPayer[12] = ucwords(strtolower($address[3]));
			}
			
			// if an address (pad to this field)
			else if (preg_match('/^\d/',$taxpayer[$i][0]) || preg_match('/^PO/',$taxpayer[$i][0])) {
				if (!isset($formPayer[7])) $formPayer[7] =  ucwords(strtolower($taxpayer[$i][0]));
				else if (!isset($formPayer[8])) $formPayer[8] =  ucwords(strtolower($taxpayer[$i][0]));
				else if (!isset($formPayer[9])) $formPayer[9] =  ucwords(strtolower($taxpayer[$i][0]));
			}
		
		$formPayer[13] = $taxpayer[1][1];
	}
		
		// extract coordinates by searching through array
		for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/EAST-(\d*) NRTH-(\d*)/', $taxpayer[$i][$j], $coord)) {
					$formPayer[14] = $coord[1];
					$formPayer[15] = $coord[2];		
				}
			}
		}
		
		// extract acres
		
			for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/ACRES *?(\d+)/', $taxpayer[$i][$j],$acres)) {
					$formPayer[16] = $acres[1];
				}
				else if (preg_match('/ACRES/', $taxpayer[$i][$j])) {
					if (preg_match('/^([0-9.]+)/', $taxpayer[$i][$j+1], $acres)) $formPayer[16] = $acres[1];
				}
			}
		}

	// extract full market value

			for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/FULL MARKET VALUE *?(\d+)/', $taxpayer[$i][$j],$value)) {
					$formPayer[17] = str_replace(',','',$value[1]);
				}
				else if (preg_match('/FULL MARKET VALUE/', $taxpayer[$i][$j])) {
					if (preg_match('/^([0-9,]+)/', $taxpayer[$i][$j+1], $value)) $formPayer[17] = str_replace(',','',$value[1]);
				}
			}
		}
		
		// extract deed book info
			for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					
										
					if (preg_match('/DEED BOOK *?(\d+) *?PG-(\d+)/', $taxpayer[$i][$j],$value)) {
						$formPayer[18] = $value[1];
						$formPayer[19] = $value[2];
					}
					else if (preg_match('/DEED BOOK *?(\d+)/', $taxpayer[$i][$j],$value)) {
						$formPayer[18] = $value[1];
						if (isset($taxpayer[$i][$j+1]) && preg_match('/^PG-(\d+)/', $taxpayer[$i][$j+1], $value)) $formPayer[19] = $value[1];
					}
				}
			}
				
			// county taxable amount
			for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					if (preg_match('/COUNTY TAXABLE VALUE/', $taxpayer[$i][$j])) $formPayer[20] = chop(str_replace(',','',$taxpayer[$i][$j+1]));
				}
			}

		// school taxable amount
			for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					if (preg_match('/SCHOOL TAXABLE VALUE/', $taxpayer[$i][$j])) $formPayer[21] = chop(str_replace(',','',$taxpayer[$i][$j+1]));
				}
			}	
		// city taxable amount
			for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					if (isset($taxpayer[$i][$j]) && preg_match('/^(CITY|TOWN)/', $taxpayer[$i][$j])) {
						if (isset($taxpayer[$i][$j+1]) && preg_match('/^TAXABLE VALUE/', $taxpayer[$i][$j+1])) $formPayer[22] =  chop(str_replace(',','',$taxpayer[$i][$j+2]));
						
					}
				}	
			}
	
		
		// field relating to solar power (for munis that have such laws)
		$formPayer[24] = '';
		for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/solar/i', $taxpayer[$i][$j])) {
					$formPayer[24] .= "{$taxpayer[$i][$j]},";
				}
			}	
		}	
		
		// STAR
		$formPayer[25] = '';
		for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/ STAR/', $taxpayer[$i][$j])) {
					$formPayer[25] .= "{$taxpayer[$i][$j]},";
				}
			}	
		}
		
		// STAR
		$formPayer[26] = '';
		for ($i = 0; $i < count($taxpayer); $i++) {
			for ($j = 0; $j < count($taxpayer[$i]); $j++) {
				if (preg_match('/(VET WAR|CW_15_VET|VETWAR|VETDIS|VETERANS)/', $taxpayer[$i][$j])) {
					$formPayer[26] .= "{$taxpayer[$i][$j]},";
				}
			}	
		}	
		
		// SCHOOL
		$formPayer[27] = $taxpayer[2][1];	
		
		// columns 28+ are special districts
		$l = 28;
		
		foreach ($specialDistType as $type) {	
			$formPayer[$l] = '';
				
			for ($i = 0; $i < count($taxpayer); $i++) {
				for ($j = 0; $j < count($taxpayer[$i]); $j++) {
					if (isset($taxpayer[$i][$j]) && preg_match('/^(\w\w)(\d\d\d) (.*?)( TO|$|\d{2,})/', $taxpayer[$i][$j],$matches)) {
						if ($matches[1] == $type) $formPayer[$l] .= "{$matches[1]}{$matches[2]} {$matches[3]} ";
					}
				}	
			}
			
			$l++;
		}
		
		
		// sort and add missing keys
		for ($i = 0; $i < count($formPayer); $i++) {
			if (!isset($formPayer[$i])) $formPayer[$i] = '';
		}
		
		
		ksort($formPayer);
		
				// shift onto the rolls county, town, village, swis
		for ($i = 0; $i < count($taxpayer); $i++) {
				
				if ($taxpayer[$i][0] != 'location') continue;
				
				// add array to line				
				for ($j = count($taxpayer[$i])-1; $j > 0; $j--) array_unshift($formPayer, $taxpayer[$i][$j]);
				
		}
		
		
		$formTax[] = $formPayer;
		
		}


		// lastly sort form by street and number
		
	    $addNum = array();
        $addSt = array();
        $own1 = array();
		for ($i = 0; $i < count($formTax); $i++) {
		  $addSt[] = $formTax[$i][6];
		  $addNum[] = $formTax[$i][5]; 
		  $own1[] =  $formTax[$i][7];
		}

		// now apply sort
		array_multisort($addSt, SORT_ASC, 
				$addNum, SORT_NUMERIC, SORT_ASC,
				$own1, SORT_ASC, 
				$formTax);
				
				
	//print_r($formTax);

	echo "\nWriting to CSV ...";

	// print out form
	$output .=  '"Tax Roll","County","Town","Village","SWIS","Tax ID","Street Number","Street Name","Owner 1","Owner 2","Owner 3","Owner 4",'
				.'"Mail Address 1","Mail Address 2","Mail Address 3","Mail City","Mail State","Mail Zip",'
				.'"Property Type","East","North","Acres","Full Market Value","Deed Book","Deed Pg",'
				.'"County Value","School Value","Town Value","Full Street",'
				.'"Solar","STAR","VETS","School",';
				
	foreach ($specialDistType as $type) {
		$output .= "\"$type\",";
	}
				
	$output .=  "\n";

	foreach ($formTax as $line) {
		$output .=  '"'.$town.'",';
		foreach ($line as $item) {
			$output .=  '"'.$item.'",';
		}
		
		$output .=  "\n";
	}
	
	// save output to file
	file_put_contents("output-csv/$town.csv", $output);
	
	echo " DONE\n";
}

// last, create a great big file
//system("cat output-csv/*.csv > all-property.csv");

system("zip output-csv.zip output-csv/*");


Real Property Tax Law 1590 requires that municipalities post their tax rolls, within 10 days of the proposed and final rolls being approved. The rolls are generally searchable PDF files, but that isn't that helpful if you are trying to search and compare multiple properties or want to use the North-East Coordinate data to make a map.

This script -- which uses the Linux program pdfttext and other common Linux commands to convert the PDF to a text file, then processes it into a .CSV file that can be opened with a GIS program such as Quantum GIS or a spreadsheet like Microsoft Excel or OpenOffice Calc.

Where in the U.S. Are You Most Likely to Be Audited by the IRS? – ProPublica

Where in the U.S. Are You Most Likely to Be Audited by the IRS? – ProPublica

Humphreys County, Mississippi, seems like an odd place for the IRS to go hunting for tax cheats. It’s a rural county in the Mississippi Delta known for its catfish farms, and more than a third of its mostly African American residents are below the poverty line. But according to a new study, it is the most heavily audited county in America. Where the IRS Audits More Income tax filings in these counties were audited at a higher rate than the nation as a whole.

As we reported last year, the IRS audits EITC recipients at higher rates than all but the richest Americans, a response to pressure from congressional Republicans to root out incorrect payments of the credit. The study estimates that Humphreys, with a median annual household income of just $26,000, is audited at a rate 51 percent higher than Loudoun County, Virginia, which boasts a median income of $130,000, the highest in the country. Kim M. Bloomquist, the author of the study, which was first published in the industry journal Tax Notes, served as a senior economist with the IRS’ research division for two decades. He decided to map the distribution of audits to illustrate the dramatic regional effects of the IRS’ emphasis on EITC audits. Because more than a third of all audits are of EITC recipients, the number of audits in each county is largely a reflection of how many taxpayers there claimed the credit, he found.

To Cut Taxes, Big-Box Stores Use ‘Dark Store Theory’

To Cut Taxes, Big-Box Stores Use ‘Dark Store Theory’

"Big-box defenders argue that the “sales approach” (what someone recently paid for a similar property) is the best way to determine a building’s value. And in many states, including Wisconsin, sales are supposed to be the first variable in the valuation equation, whenever possible. Therefore, retailers’ lawyers say, a Sam’s Club valued at $11 million is overvalued, because its neighbors are selling for a third of that amount. In a real estate market that’s oversaturated with retail closures, bankruptcies, and vacancies galore, they insist, no one wants a big box store anymore. If you just look at the sales prices, they are often not wrong."

"But assessors say that this misses what gives a functional property its value. Location is everything in real estate—there may be a good reasons why some of those stores went dark. Besides, the market for big boxes is too small to rely solely on sales; construction costs and property incomes also have to be taken into account. And many of these vacant and depreciated properties would need major repairs to achieve a state of “highest and best use,” which would be a more appropriate comparison for an open and fully updated store."

"Besides, there’s something plainly illogical about the argument. “Do you want me to value your house as if it’s closed and boarded up?” said Krause. So, case closed? Not quite. The vast majority of dark store appeals brought by big boxes—many of which ask for write-downs of 50 percent—are being settled for a lower valuation, probably in the ballpark of 85 percent, Thomas Hamilton, a professor of real estate at Roosevelt University, told me. Many assessors strive to be conservative in their estimates, so they usually try to find a happy medium when taxpayers protest. Plus, it’s costly to litigate."